diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..bed0738c7eeb449bca98b5d2f33c89a1ee56349a --- /dev/null +++ b/.gitattributes @@ -0,0 +1,60 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.avro filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.lz4 filter=lfs diff=lfs merge=lfs -text +*.mds filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +# Audio files - uncompressed +*.pcm filter=lfs diff=lfs merge=lfs -text +*.sam filter=lfs diff=lfs merge=lfs -text +*.raw filter=lfs diff=lfs merge=lfs -text +# Audio files - compressed +*.aac filter=lfs diff=lfs merge=lfs -text +*.flac filter=lfs diff=lfs merge=lfs -text +*.mp3 filter=lfs diff=lfs merge=lfs -text +*.ogg filter=lfs diff=lfs merge=lfs -text +*.wav filter=lfs diff=lfs merge=lfs -text +# Image files - uncompressed +*.bmp filter=lfs diff=lfs merge=lfs -text +*.gif filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text +*.tiff filter=lfs diff=lfs merge=lfs -text +# Image files - compressed +*.jpg filter=lfs diff=lfs merge=lfs -text +*.jpeg filter=lfs diff=lfs merge=lfs -text +*.webp filter=lfs diff=lfs merge=lfs -text +# Video files - compressed +*.mp4 filter=lfs diff=lfs merge=lfs -text +*.webm filter=lfs diff=lfs merge=lfs -text diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..d645695673349e3947e8e5ae42332d0ac3164cd7 --- /dev/null +++ b/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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Contains authentic PNGs, parameters, seeds, measured latency/allocator values, SHA-256 and diagnostic records. **No speedup or text-correctness claim follows from file size or image similarity alone.** + +## How to read these reference examples + +These PNG/JPG images and descriptive measurements are **reference examples**, not a +standardized leaderboard or dataset-loader API. Browse the gallery and associated +results in **Files and versions**; reproducing the experiments is **not required** +to try any checkpoint. + +Some samples intentionally show misspellings, changed compositions and failed runs. +They are not a certified-quality showcase. + +**License and provenance:** This dataset's original curation, generated samples, associated results and metadata are released under **[Apache License 2.0](LICENSE)** by the dataset publisher. The underlying [MOSS-Image-SFT](https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT) and [Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) source models use Apache-2.0. Any third-party content (including the one archived historical HF comparison sheet in historical_references/) is supplied as reference material; **its pre-existing rights are not relicensed** by this dataset. Users should verify rights before independently redistributing third-party imagery. + +Results depend on the hardware, sampler, step count, seed, encoder and precision. +Do not merge the original 50-step SFT, experimental 10-step DPM++2M and four-step +student-adapter trials into one speed or image-quality ranking. PSNR, SSIM and +LPIPS indicate divergence from a reference; they do not score Polish spelling, +readability, aesthetics or compatibility with a new GPU. + +All eleven component releases are experimental. See each model card for +format-specific validation gaps and further-testing recommendations. Missing native-kernel +validation means unverified on the recorded setup, not a universal incompatibility. + +## Checkpoint comparison + +All eight DiT files derive from [OpenMOSS-Team/MOSS-Image-SFT](https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT) at `fc5de0d56fc910cbca6f6625a70f5f582b26deb1` and preserve the original model (50-step reference). All use actual TorchAO checkpoint serialization, **not** a student/LoRA export. + +| DiT checkpoint | Weight GiB | Quantized Linear | Reference evidence and testing status | +|---|---:|---:|---| +| [INT8-WO-Core](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-INT8-WO-Core) | 5.470 | 228/269 | 5 SFT50 pairs; broader text/visual testing recommended | +| [FP8-WO-Core](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-FP8-WO-Core) | 5.463 | 228/269 | 5 SFT50 pairs; broader text/visual testing recommended | +| [FP8-WO-Max](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-FP8-WO-Max) | 4.739 | 269/269 | 5 SFT50 pairs; broader visual testing recommended | +| [FP8-W8A8-Row-Core](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-FP8-W8A8-Row-Core) | 5.464 | 228/269 | Original SFT50 image test unavailable; native runtime requires testing | +| [FP8-W8A8-Row-Max](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-FP8-W8A8-Row-Max) | 4.739 | 269/269 | Original SFT50 image test unavailable; native runtime requires testing | +| [FP8-W8A8-Tensor-Core](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-FP8-W8A8-Tensor-Core) | 5.459 | 228/269 | 4 original SFT50 images on SM120; additional tests required | +| [NVFP4-Core](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-NVFP4-Core) | 3.706 | 228/269 | No validated native FP4 SFT50 images; native runtime requires testing | +| [NVFP4-Max](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-NVFP4-Max) | 2.663 | 269/269 | No validated native FP4 SFT50 images; native runtime requires testing | + +BF16 original DiT storage: **9.467 GiB**. Storage size is **not** full pipeline size, resident GPU VRAM or execution throughput. W8A8 and NVFP4 native kernel support was missing in the recorded SM80 original-50-step benchmark, not on every GPU universally. + +Independent original components: [Qwen FP8-WO](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-Qwen3.5-FP8-WO), [VAE FP16](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-VAE-FP16), [VAE BF16](https://huggingface.co/WiktorMatuszek/MOSS-Image-SFT-VAE-BF16). + +## Original full SFT — 50-step, seed-matched smoke test + +**5 images** at 1024px, CFG 3 and seed 42, original model sampler, CMP 170HX / SM80. Median latency and peak *allocated* CUDA are scope-specific; quality metrics measure distance to BF16. + +| Checkpoint | Median s/image | Peak CUDA allocated GiB | SSIM vs BF16 ↑ | LPIPS ↓ | +|---|---:|---:|---:|---:| +| BF16 original | 53.176 | 12.542 | Reference | Reference | +| INT8-WO Core | 58.824 | 8.544 | 0.89499 | 0.05729 | +| FP8-WO Core | 63.361 | 8.538 | 0.84926 | 0.08454 | +| FP8-WO Max | 65.320 | 7.816 | 0.78998 | 0.10494 | + +![All eight original model quantizations: only measured outputs displayed; missing results explicitly marked](research/moss50-20261021/grids/REAL_IMAGE_COMPARISON_GRID.png) + +[Further source-matched grids and absolute difference maps](https://huggingface.co/datasets/WiktorMatuszek/moss-zimage-quantization-benchmarks/tree/main/research/moss50-20261021/grids). + +## Independent experimental 10-step study + +**DPM++2M10, 1024px, CFG 3, seed 42; 16 real images per variant.** Not the original 50-step SFT protocol and not the 4-step student adapter. Same CMP 170HX / SM80 environment. + +| DiT | Median s/image | Median CUDA reserved GiB | SSIM vs BF16 ↑ | Learned LPIPS ↓ | +|---|---:|---:|---:|---:| +| Original BF16 | 11.029 | 14.156 | Reference | Reference | +| INT8-WO Core | 12.074 | 10.344 | 0.9097 | 0.053268 | +| FP8-WO Core | 12.991 | 10.490 | 0.8559 | 0.073368 | + +On this setup the packed models saved reserved CUDA memory but did **not** beat BF16 on runtime. Other GPU/kernel choices need distinct measurements. + +![True generated Polish letters: BF16 vs INT8 vs FP8 at identical prompts and seed](research/turbo10-20261022/images/pl_exact_original_images_1024.jpg) + +![True photo scene retention for same-seed BF16 versus quantizations](research/turbo10-20261022/images/scene_retention_original_images_1024.jpg) + +[All 32 paired image scores](research/turbo10-20261022/data/ALL_PAIR_METRICS.csv) · [pretrained LPIPS](research/turbo10-20261022/data/LPIPS_PRETRAINED_PAIR_REPORT.json) · [complete aggregate limitations](research/turbo10-20261022/data/TURBO10_QUANT_PAIR_RESULT.json). + +## Raw generation archive (other GPU and Z-Image) + +`runs/moss-image-20261021/` holds a separate RTX 5060 Ti experiment with original 50-step MOSS-SFT, four-step student adapters, two-step kernel probes, native/high-resolution generations, upscales, and independent Z-Image Turbo API outputs. **These have different timing scopes, sampling policies and conditioning environments. They are not one homogeneous benchmark**. Historical reference discrepancy on “RIVER BAKERY” also occurred with original BF16 under local runtime controls; it is not evidence that quantization alone caused the issue. + +| Subset | Images | Purpose | +|---|---:|---| +| `quality` | 268 | Original generated outputs and parameters | +| `upscales` | 157 | Upscaled images plus parent references | +| `diagnostics` | 12 | Technical execution probes (not output-quality evidence) | +| `historical_references` | 1 | Archived comparison reference (not current-device latency) | + +`runs/moss-image-20261021/records/measurements.jsonl` preserves raw successful and failed attempts. `quality/metadata.jsonl` preserves image hashes, expected text, model/precision, steps/CFG, seed, GPU and timings where measured; missing values remain null. + +**Limitations:** PSNR/SSIM/LPIPS measure similarity to a reference PNG, **not** correctness of Polish characters, naturalness, real-world image quality or independent blind human preference. Store original component hashes, exact sampling protocol and device details with any derived figure. This repository is private research evidence, not a validated public model-quality leaderboard. + +**Research suites and sanitized diagnostics.** The [50-step prompt suite](research/moss50-20261021/benchmark_suite.json) and [style benchmark suite](research/moss50-20261021/style_benchmark_suite.json) are stored once here, rather than repeated across eight checkpoint repos. A [compact compatibility summary](research/device-compatibility-20261021/summary.json) accompanies raw individual runs. Server filesystem prefixes in diagnostics were redacted; numeric results, prompts, SHA-256 image hashes and status fields remain. Dataset remains private pending separate image-rights review. diff --git a/research/device-compatibility-20261021/summary.json b/research/device-compatibility-20261021/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..afdbc55d26334f72eb4e00dfd6ea4b59ba0b5e33 --- /dev/null +++ b/research/device-compatibility-20261021/summary.json @@ -0,0 +1,313 @@ +{ + "schema": "device_compat_summary_v1", + "source": "MOSS-SFT local image study; full per-image data in runs/moss-image-20261021/records/measurements.jsonl", + "notice": "Mixed hardware/protocols. Two-step diagnostics and four-step student runs do not certify original SFT50 quality.", + "variants": [ + { + "variant": "MOSS-Image-SFT-FP8-W8A8-Tensor-Core", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "eager", + "override": "None", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 4 + }, + { + "steps": "50", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 4 + } + ] + } + ] + }, + { + "variant": "MOSS-Image-SFT-FP8-WO-Core", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "compile", + "override": "None", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "error", + "count": 1 + }, + { + "steps": "4", + "mode": "eager", + "override": "None", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 42 + }, + { + "steps": "50", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 28 + }, + { + "steps": "50", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 3 + } + ] + } + ] + }, + { + "variant": "MOSS-Image-SFT-FP8-WO-Max", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "eager", + "override": "None", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 8 + }, + { + "steps": "50", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 4 + } + ] + } + ] + }, + { + "variant": "MOSS-Image-SFT-INT8-WO-Core", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "eager", + "override": "None", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 38 + }, + { + "steps": "50", + "mode": "compile", + "override": "None", + "student": "None", + "status": "ok", + "count": 2 + }, + { + "steps": "50", + "mode": "eager", + "override": "None", + "student": "None", + "status": "ok", + "count": 26 + } + ] + } + ] + }, + { + "variant": "MOSS-Image-SFT-NVFP4-Core", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "nvfp4-weight-only", + "student": "None", + "status": "error", + "count": 2 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "error", + "count": 2 + }, + { + "steps": "2", + "mode": "eager", + "override": "nvfp4-weight-only", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "eager", + "override": "nvfp4-weight-only", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 4 + } + ] + } + ] + }, + { + "variant": "MOSS-Image-SFT-NVFP4-Max", + "tests": [ + { + "source": "compatibility.json", + "outcomes": [ + { + "steps": "2", + "mode": "compile", + "override": "nvfp4-weight-only", + "student": "None", + "status": "error", + "count": 2 + }, + { + "steps": "2", + "mode": "eager", + "override": "None", + "student": "None", + "status": "error", + "count": 2 + }, + { + "steps": "2", + "mode": "eager", + "override": "nvfp4-weight-only", + "student": "None", + "status": "ok", + "count": 1 + } + ] + }, + { + "source": "results.json", + "outcomes": [ + { + "steps": "4", + "mode": "eager", + "override": "nvfp4-weight-only", + "student": "{'sha256': '154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f', 'dtype': 'float32', 'merged': False, 'helper_sha256': '6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3'}", + "status": "ok", + "count": 4 + } + ] + } + ] + } + ] +} diff --git a/research/moss50-20261021/benchmark_suite.json b/research/moss50-20261021/benchmark_suite.json new file mode 100644 index 0000000000000000000000000000000000000000..7e7621c83d627c2ebded27cd68e9567e3f2e8bc4 --- /dev/null +++ b/research/moss50-20261021/benchmark_suite.json @@ -0,0 +1,159 @@ +{ + "cases": [ + { + "category": "pl_exact", + "description": "outdoor sign", + "expected_text": "Wróżka z Łęczycy", + "id": "pl_01_wrozka", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A weathered wooden village road sign on a clear autumn morning, realistic grain and angled warm sunlight.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Wróżka z Łęczycy\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": true + }, + { + "category": "pl_exact", + "description": "shop sign", + "expected_text": "Żółć gęślą jaźń", + "id": "pl_02_zolc", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A white porcelain shop sign on a dark green historic facade, softly lit, shallow depth of field.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Żółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": true + }, + { + "category": "pl_exact", + "description": "rail plate", + "expected_text": "Łódź – Żyrardów", + "id": "pl_03_lodz", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A red vintage railway destination plate on a dark blue train, natural weathering.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Łódź – Żyrardów\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "pl_exact", + "description": "paper typography", + "expected_text": "Zażółć gęślą jaźń", + "id": "pl_04_wazny", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A folded letterpress invitation on cream textured paper, realistic macro photograph.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Zażółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "pl_exact", + "description": "storefront", + "expected_text": "Świeże pączki", + "id": "pl_05_sprzedaz", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"Realistic modern storefront with black metal letters on cream marble, overcast outdoor street.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Świeże pączki\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "pl_exact", + "description": "handwriting", + "expected_text": "Książę i księżniczka", + "id": "pl_06_jezyk", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A handwritten memo on a study desk beside a mechanical pencil and a cup of tea.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Książę i księżniczka\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "pl_exact", + "description": "two lines", + "expected_text": "GÓRA\nŁÓDŹ", + "id": "pl_07_dwa_wiersze", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A square enamel noticeboard on a historic Kraków street, two rows separated by a line break.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"GÓRA\\nŁÓDŹ\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "pl_exact", + "description": "long literal", + "expected_text": "Pchnąć w tę łódź jeża", + "id": "pl_08_long", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A crisp printed museum exhibit label on matte ivory paper, in a glass display case.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Pchnąć w tę łódź jeża\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "en_exact", + "description": "neon sign", + "expected_text": "FRESH COFFEE", + "id": "en_01_cafe", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"An elegantly lit downtown coffee shop with warm cinematic reflections and a legible neon window sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"FRESH COFFEE\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": true + }, + { + "category": "en_exact", + "description": "metal sign", + "expected_text": "OPEN TODAY", + "id": "en_02_studio", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A minimalist photography studio product photo of a brushed aluminum sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"OPEN TODAY\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "en_exact", + "description": "poster", + "expected_text": "MIDNIGHT RADIO", + "id": "en_03_poster", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-contrast modern gig poster pasted to a rainy concrete wall.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"MIDNIGHT RADIO\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": false + }, + { + "category": "no_text", + "description": "blank wooden sign", + "expected_text": null, + "id": "notext_01_blank", + "prompt": "A photograph of a completely blank unpainted wooden sign in a mountain meadow. No lettering, no symbols, no logo, absolutely no writing.", + "smoke": true + }, + { + "category": "no_text", + "description": "still life", + "expected_text": null, + "id": "notext_02_ceramics", + "prompt": "Professional studio photograph of three glazed ceramic bowls, a folded linen napkin and dramatic soft shadows. No symbols or text anywhere.", + "smoke": false + }, + { + "category": "scene_retention", + "description": "night city", + "expected_text": null, + "id": "scene_01_city", + "prompt": "Photorealistic rainy cobblestone alley at blue hour with cinematic reflections, a parked bicycle, mossy stonework and warm windows, no readable writing.", + "smoke": true + }, + { + "category": "scene_retention", + "description": "portrait", + "expected_text": null, + "id": "scene_02_portrait", + "prompt": "Detailed editorial photograph of a curly-haired woman in a yellow raincoat standing in a misty forest, atmospheric light, natural face, no text.", + "smoke": false + }, + { + "category": "scene_retention", + "description": "architecture", + "expected_text": null, + "id": "scene_03_architecture", + "prompt": "Brutalist concrete library in fog at dawn, strong geometry, fine-grain analog photographic realism, tiny plants in the foreground, no lettering.", + "smoke": false + } + ], + "comment": "Frozen prompts, exact same seeds/settings for BF16 source and all quantized variants; score text and scene independently. NOT model-generated evaluation results.", + "model_family": "ORIGINAL_FULL_SFT_NOT_4STEP_NOT_LORA", + "reference": { + "cfg": 3, + "height": 1024, + "negative_prompt": "", + "scheduler": "flow-matching Euler", + "shift": 5, + "steps": 50, + "uncond_skip_layers": [ + 22 + ], + "width": 1024 + }, + "schema_version": 1, + "seeds": { + "full": [ + 42, + 2026 + ], + "smoke": [ + 42 + ] + }, + "source": "OpenMOSS-Team/MOSS-Image-SFT", + "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", + "suite_id": "moss-image-sft-quantization-comparison-v1" +} diff --git a/research/moss50-20261021/grids/AMPLIFIED_4X_DIFFERENCE_GRID.png b/research/moss50-20261021/grids/AMPLIFIED_4X_DIFFERENCE_GRID.png new file mode 100644 index 0000000000000000000000000000000000000000..ddb79dc9a40043ee37b2f860fa639b766d28a9d0 --- /dev/null +++ b/research/moss50-20261021/grids/AMPLIFIED_4X_DIFFERENCE_GRID.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eaad73d9b002705826798b7ea61d51433a9839ebb1f2963a10aa9aa8f4bba981 +size 2256894 diff --git a/research/moss50-20261021/grids/REAL_IMAGE_COMPARISON_GRID.png b/research/moss50-20261021/grids/REAL_IMAGE_COMPARISON_GRID.png new file mode 100644 index 0000000000000000000000000000000000000000..0690a165294ae1fee18e01a15fbce626a6076e9c --- /dev/null +++ b/research/moss50-20261021/grids/REAL_IMAGE_COMPARISON_GRID.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:95cf18a80e5af15aa862877a8b687dd04f526f5db8b82feb127caa77480337e1 +size 2593297 diff --git a/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_2026.png b/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_2026.png new file mode 100644 index 0000000000000000000000000000000000000000..b662109cb7b3df52f6d19fe758e2d58f6e9af5d5 --- /dev/null +++ b/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_2026.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1896c6b7955ba18f066f00e15a5e0e1d9fed1d8a7b301308ef888dc824faff5a +size 1020999 diff --git a/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_42.png b/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_42.png new file mode 100644 index 0000000000000000000000000000000000000000..91d7fb0afe59e1aaa433b31ee1a1a4d3af7f259d --- /dev/null +++ b/research/moss50-20261021/grids/STYLE_DIVERSITY_DIFF_X4_SEED_42.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a2b5e171e6d234ed3ff92d7134d470f142e1c357f39ea8dfc6ec42c22e7913f8 +size 1000212 diff --git a/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_2026.png b/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_2026.png new file mode 100644 index 0000000000000000000000000000000000000000..ffd374c2eecc9e236faf9fed880d92458c2964b7 --- /dev/null +++ b/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_2026.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a529a7213abf97da6ede67181c154aec0c7534a700d04b2186d804caf06b62ff +size 1162841 diff --git a/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_42.png b/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_42.png new file mode 100644 index 0000000000000000000000000000000000000000..85e60cce21e30fc33477394966ac15a66aad0a12 --- /dev/null +++ b/research/moss50-20261021/grids/STYLE_DIVERSITY_REAL_IMAGES_SEED_42.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d92a47654cde8d36e908712b635e83f0909618abbaaa507a52ff3928e81b1c8f +size 1214461 diff --git a/research/moss50-20261021/style_benchmark_suite.json b/research/moss50-20261021/style_benchmark_suite.json new file mode 100644 index 0000000000000000000000000000000000000000..466c4b98382d7f062c55aa02572e17924021199b --- /dev/null +++ b/research/moss50-20261021/style_benchmark_suite.json @@ -0,0 +1,47 @@ +{ + "schema_version": 1, + "suite_id": "moss-image-sft-style-diversity-v1", + "source": "OpenMOSS-Team/MOSS-Image-SFT", + "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", + "model_family": "ORIGINAL_FULL_SFT_NOT_4STEP_NOT_LORA", + "reference": { + "height": 1024, + "width": 1024, + "steps": 50, + "cfg": 3, + "shift": 5, + "negative_prompt": "", + "uncond_skip_layers": [ + 22 + ], + "scheduler": "flow-matching Euler" + }, + "seeds": { + "smoke": [ + 42 + ], + "full": [ + 42, + 2026 + ] + }, + "comment": "Two fixed additional non-Polish prompts evaluating illustrated anime character quality and photorealistic English storefront text/fine textures. Generate actual MOSS-SFT BF16 and quantized DiT outputs with same seed/conditioning; no third-party reference images used.", + "cases": [ + { + "id": "style_01_anime_woman", + "category": "anime_illustration", + "description": "Original anime illustration of adult woman; expressive face, precise hair strands, fabric, neon lighting, gradients and composition; no text.", + "expected_text": null, + "prompt": "An original, high-quality anime illustration, cinematic medium portrait of an adult young woman aged 24 with expressive violet eyes and long dark brown hair flowing naturally in the evening breeze, detailed individual hair strands and delicate accessories, wearing a layered fashionable dark blue jacket and light blouse. She turns toward the viewer with a subtle friendly smile on a bustling lantern-lit city street at blue hour, intricate background architecture, neon reflections on wet stone paving, shallow depth, natural balanced anatomy and hands, exquisite clean line art and controlled cel shading, rich soft gradients, highly detailed face, fabrics, light and shadows, vivid but tasteful color palette. No text, no signs with lettering, no logos, no watermarks. Entirely original character and setting, no existing franchise or copyrighted character.", + "smoke": true + }, + { + "id": "style_02_river_bakery", + "category": "photoreal_english", + "description": "Photorealistic bakery shopfront with single clear English sign; measures textures, reflections, light and typography.", + "expected_text": "RIVER BAKERY", + "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-end photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood facade, large glass windows with layered city reflections, intricate golden croissants, artisan breads in a display, elegant brass lamps, stone sidewalk with dappled tree shadows, realistic metal, glass, fabric and bread textures, rich dynamic range and sharp yet natural fine detail. Frontal slightly angled wide view, no logos and no extra printed or handwritten text beyond the main bakery sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"one beautifully letterspaced legible gold serif sign on the dark fascia above the glass storefront\",\"text\":\"RIVER BAKERY\",\"bbox\":[-380,-380,-200,380]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", + "smoke": true + } + ] +} diff --git a/research/turbo10-20261022/data/ALL_PAIR_METRICS.csv b/research/turbo10-20261022/data/ALL_PAIR_METRICS.csv new file mode 100644 index 0000000000000000000000000000000000000000..dfe421a3f0e2e4005211be268bb79d8230a0aa81 --- /dev/null +++ b/research/turbo10-20261022/data/ALL_PAIR_METRICS.csv @@ -0,0 +1,33 @@ +variant,case,seed,category,original_sha256,quant_sha256,quant_seconds,bf16_seconds,quant_vram_reserved_gib,bf16_vram_reserved_gib,mae_8bit,psnr_db,ssim_rgb,original_gradient_mean,original_dark_fraction,original_saturated_fraction,candidate_gradient_mean,candidate_dark_fraction,candidate_saturated_fraction,center_mae_8bit,center_psnr_db,center_ssim_rgb,center_original_gradient_mean,center_original_dark_fraction,center_original_saturated_fraction,center_candidate_gradient_mean,center_candidate_dark_fraction,center_candidate_saturated_fraction +int8wo-core,pl_01_wrozka,42,pl_exact,a42925aa6519d88bba9bef93a98c2a582fde37b59b9c58d5030604e039ecb598,1f6b49be85a143a3e09e4cb591deafd754c3150d0d9238459318b62ad698d5a3,12.335218205058482,14.859219908015803,10.34375,14.15625,8.26888,22.72167,0.89784,56.78836,0.01866,0.0,56.29056,0.02548,0.0,11.78437,19.40743,0.83489,75.93,0.01329,0.0,77.58973,0.01574,0.0 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"REQUIRES_PHYSICAL_VISUAL_LITERALS_AND_PHOTO" + } + ], + "median_original_s": 53.17557, + "median_turbo_s": 11.031110934971366, + "median_ssim": 0.5848186612129211, + "median_lpips": 0.2639220356941223 +} diff --git a/research/turbo10-20261022/data/TURBO10_QUANT_PAIR_RESULT.json b/research/turbo10-20261022/data/TURBO10_QUANT_PAIR_RESULT.json new file mode 100644 index 0000000000000000000000000000000000000000..15fabedd50140dc7067cbc1b51c1935e3c8f0375 --- /dev/null +++ b/research/turbo10-20261022/data/TURBO10_QUANT_PAIR_RESULT.json @@ -0,0 +1,41 @@ +{ + "source": "Original local CMP 170 HX paired study; source filesystem path withheld.", + "basis": "real 1024x1024 same prompt+seed DPM++10", + "limitations": [ + "PSNR/SSIM are divergence not absolute quality", + "1 seed; no independent Polish OCR/photo grader", + "CMP170HX SM80 not RTX5060Ti SM120" + ], + "results": { + "bf16-original": { + "images": 16, + "median_image_sec": 11.029, + "median_cuda_reserved_gib": 14.156, + 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"candidate": "conditioning-study-original.pt", "case": "style_01_anime_woman", "exact": false, "mae": 0.019177868962287903, "max_abs": 0.5, "cosine": 0.999815821647644}, {"reference": "conditioning-study-legacy-gpu.pt", "candidate": "conditioning-study-original.pt", "case": "style_02_river_bakery", "exact": false, "mae": 0.020320774987339973, "max_abs": 0.59375, "cosine": 0.999784529209137}, {"reference": "conditioning-study-legacy-gpu.pt", "candidate": "conditioning-study-original.pt", "case": "pl_natural_paczki", "exact": false, "mae": 0.020894311368465424, "max_abs": 1.0, "cosine": 0.99982750415802}, {"reference": "conditioning-study-legacy-gpu.pt", "candidate": "conditioning-study-original.pt", "case": "pl_menu_prices", "exact": false, "mae": 0.02274811826646328, "max_abs": 0.75, "cosine": 0.9997996687889099}, {"reference": "conditioning-study-legacy-gpu.pt", "candidate": "conditioning-study-original.pt", "case": "pl_poster_multiline", "exact": false, "mae": 0.023334123194217682, "max_abs": 0.75, "cosine": 0.999786376953125}, {"reference": "conditioning-study-legacy-gpu.pt", "candidate": "conditioning-study-original.pt", "case": "pl_long_sentence", "exact": false, "mae": 0.023244371637701988, "max_abs": 0.75, "cosine": 0.9997766017913818}]} \ No newline at end of file diff --git a/runs/moss-image-20261021/context/prompt_control_suite.json b/runs/moss-image-20261021/context/prompt_control_suite.json new file mode 100644 index 0000000000000000000000000000000000000000..5ab08c00a910ef3686adee3ea6953e968e8bc9d6 --- /dev/null +++ b/runs/moss-image-20261021/context/prompt_control_suite.json @@ -0,0 +1 @@ +{"suite_id": "kwant-moss-plain-prompt-controls-v1", "seeds": [42, 2026], "note": "Additional prompt-format and language controls; these prompts differ from the historical HF reference.", "cases": [{"id": "bakery_plain_en", "description": "bakery_plain_en", "category": "plain_prompt_control", "expected_text": "RIVER BAKERY", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text."}, {"id": "bakery_plain_pl", "description": "bakery_plain_pl", "category": "plain_prompt_control", "expected_text": "RIVER BAKERY", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów."}, {"id": "paczki_plain_pl", "description": "paczki_plain_pl", "category": "plain_prompt_control", "expected_text": "ŚWIEŻE PĄCZKI", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów."}, {"id": "menu_plain_pl", "description": "menu_plain_pl", "category": "plain_prompt_control", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów."}]} \ No newline at end of file diff --git a/runs/moss-image-20261021/context/study_suite.json b/runs/moss-image-20261021/context/study_suite.json new file mode 100644 index 0000000000000000000000000000000000000000..cd8b25e80e8d44447c6f53051281d008976b50da --- /dev/null +++ b/runs/moss-image-20261021/context/study_suite.json @@ -0,0 +1 @@ +{"suite_id": "kwant-moss-zimage-local-v1", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "seeds": [42, 2026], "cases": [{"category": "pl_exact", "description": "outdoor sign", "expected_text": "Wróżka z Łęczycy", "id": "pl_01_wrozka", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A weathered wooden village road sign on a clear autumn morning, realistic grain and angled warm sunlight.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Wróżka z Łęczycy\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": true}, {"category": "pl_exact", "description": "shop sign", "expected_text": "Żółć gęślą jaźń", "id": "pl_02_zolc", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A white porcelain shop sign on a dark green historic facade, softly lit, shallow depth of field.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Żółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": true}, {"category": "pl_exact", "description": "rail plate", "expected_text": "Łódź – Żyrardów", "id": "pl_03_lodz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A red vintage railway destination plate on a dark blue train, natural weathering.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Łódź – Żyrardów\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "pl_exact", "description": "paper typography", "expected_text": "Zażółć gęślą jaźń", "id": "pl_04_wazny", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A folded letterpress invitation on cream textured paper, realistic macro photograph.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Zażółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "pl_exact", "description": "storefront", "expected_text": "Świeże pączki", "id": "pl_05_sprzedaz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"Realistic modern storefront with black metal letters on cream marble, overcast outdoor street.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Świeże pączki\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "pl_exact", "description": "handwriting", "expected_text": "Książę i księżniczka", "id": "pl_06_jezyk", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A handwritten memo on a study desk beside a mechanical pencil and a cup of tea.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Książę i księżniczka\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "pl_exact", "description": "two lines", "expected_text": "GÓRA\nŁÓDŹ", "id": "pl_07_dwa_wiersze", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A square enamel noticeboard on a historic Kraków street, two rows separated by a line break.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"GÓRA\\nŁÓDŹ\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "pl_exact", "description": "long literal", "expected_text": "Pchnąć w tę łódź jeża", "id": "pl_08_long", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A crisp printed museum exhibit label on matte ivory paper, in a glass display case.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Pchnąć w tę łódź jeża\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "en_exact", "description": "neon sign", "expected_text": "FRESH COFFEE", "id": "en_01_cafe", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"An elegantly lit downtown coffee shop with warm cinematic reflections and a legible neon window sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"FRESH COFFEE\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": true}, {"category": "en_exact", "description": "metal sign", "expected_text": "OPEN TODAY", "id": "en_02_studio", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A minimalist photography studio product photo of a brushed aluminum sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"OPEN TODAY\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "en_exact", "description": "poster", "expected_text": "MIDNIGHT RADIO", "id": "en_03_poster", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-contrast modern gig poster pasted to a rainy concrete wall.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"MIDNIGHT RADIO\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": false}, {"category": "no_text", "description": "blank wooden sign", "expected_text": null, "id": "notext_01_blank", "prompt": "A photograph of a completely blank unpainted wooden sign in a mountain meadow. No lettering, no symbols, no logo, absolutely no writing.", "smoke": true}, {"category": "no_text", "description": "still life", "expected_text": null, "id": "notext_02_ceramics", "prompt": "Professional studio photograph of three glazed ceramic bowls, a folded linen napkin and dramatic soft shadows. No symbols or text anywhere.", "smoke": false}, {"category": "scene_retention", "description": "night city", "expected_text": null, "id": "scene_01_city", "prompt": "Photorealistic rainy cobblestone alley at blue hour with cinematic reflections, a parked bicycle, mossy stonework and warm windows, no readable writing.", "smoke": true}, {"category": "scene_retention", "description": "portrait", "expected_text": null, "id": "scene_02_portrait", "prompt": "Detailed editorial photograph of a curly-haired woman in a yellow raincoat standing in a misty forest, atmospheric light, natural face, no text.", "smoke": false}, {"category": "scene_retention", "description": "architecture", "expected_text": null, "id": "scene_03_architecture", "prompt": "Brutalist concrete library in fog at dawn, strong geometry, fine-grain analog photographic realism, tiny plants in the foreground, no lettering.", "smoke": false}, {"id": "style_01_anime_woman", "category": "anime_illustration", "description": "Original anime illustration of adult woman; expressive face, precise hair strands, fabric, neon lighting, gradients and composition; no text.", "expected_text": null, "prompt": "An original, high-quality anime illustration, cinematic medium portrait of an adult young woman aged 24 with expressive violet eyes and long dark brown hair flowing naturally in the evening breeze, detailed individual hair strands and delicate accessories, wearing a layered fashionable dark blue jacket and light blouse. She turns toward the viewer with a subtle friendly smile on a bustling lantern-lit city street at blue hour, intricate background architecture, neon reflections on wet stone paving, shallow depth, natural balanced anatomy and hands, exquisite clean line art and controlled cel shading, rich soft gradients, highly detailed face, fabrics, light and shadows, vivid but tasteful color palette. No text, no signs with lettering, no logos, no watermarks. Entirely original character and setting, no existing franchise or copyrighted character.", "smoke": true}, {"id": "style_02_river_bakery", "category": "photoreal_english", "description": "Photorealistic bakery shopfront with single clear English sign; measures textures, reflections, light and typography.", "expected_text": "RIVER BAKERY", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-end photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood facade, large glass windows with layered city reflections, intricate golden croissants, artisan breads in a display, elegant brass lamps, stone sidewalk with dappled tree shadows, realistic metal, glass, fabric and bread textures, rich dynamic range and sharp yet natural fine detail. Frontal slightly angled wide view, no logos and no extra printed or handwritten text beyond the main bakery sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"one beautifully letterspaced legible gold serif sign on the dark fascia above the glass storefront\",\"text\":\"RIVER BAKERY\",\"bbox\":[-380,-380,-200,380]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "smoke": true}, {"id": "pl_natural_paczki", "category": "pl_natural", "description": "ŚWIEŻE PĄCZKI", "expected_text": "ŚWIEŻE PĄCZKI", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks."}, {"id": "pl_menu_prices", "category": "pl_natural", "description": "MENU / Kawa 12,50 zł / Pączek 7,00 zł", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text."}, {"id": "pl_poster_multiline", "category": "pl_natural", "description": "JESIEŃ W ŁODZI / 21 PAŹDZIERNIKA / WSTĘP WOLNY", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks."}, {"id": "pl_long_sentence", "category": "pl_natural", "description": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text."}], "note": "Identical literal prompts and seeds across backends. Pixel fidelity is not text correctness. 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Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. 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Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.095644961111248, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "6a9515776d15e7dc5ea91c20eedf1df40e070e7db2fdc903864f1441738de77e", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_poster_multiline\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T17:37:00.363403+00:00\", \"finished_at\": \"2026-10-21T17:37:22.459881+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.095644961111248, \"image\": \"./zimage_pl_poster_multiline_1024x1024_12s_42.png\", \"sha256\": \"6a9515776d15e7dc5ea91c20eedf1df40e070e7db2fdc903864f1441738de77e\"}"} +{"file_name": "images/69f502e2a86ca3601fe8.png", "image_id": "69f502e2a86ca3601fe8", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.230086100287735, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "d1779cbb7674edeb6bbde6d2ef46839d257076d000852dbf525a648a2fe863cf", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_long_sentence\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"42cdd9f49317e3a8a71484e31487bb412a61c0594d34d3e18900e94ca64b3478\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T17:37:22.460267+00:00\", \"finished_at\": \"2026-10-21T17:37:44.691517+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.230086100287735, \"image\": \"./zimage_pl_long_sentence_1024x1024_12s_42.png\", \"sha256\": \"d1779cbb7674edeb6bbde6d2ef46839d257076d000852dbf525a648a2fe863cf\"}"} +{"file_name": "images/c3400ca975221d02d61a.png", "image_id": "c3400ca975221d02d61a", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_01_wrozka", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A weathered wooden village road sign on a clear autumn morning, realistic grain and angled warm sunlight.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Wróżka z Łęczycy\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Wróżka z Łęczycy", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.337613685056567, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "be2a49832d14b82e3cbbfa7846a85c04d9217fd6b183336f426c7b8b778af3c1", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_01_wrozka\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:37:44.692051+00:00\", \"finished_at\": \"2026-10-21T17:38:07.031248+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.337613685056567, \"image\": \"./zimage_pl_01_wrozka_1024x1024_12s_2026.png\", \"sha256\": \"be2a49832d14b82e3cbbfa7846a85c04d9217fd6b183336f426c7b8b778af3c1\"}"} +{"file_name": "images/d41570c28100a135382a.png", "image_id": "d41570c28100a135382a", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_02_zolc", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A white porcelain shop sign on a dark green historic facade, softly lit, shallow depth of field.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Żółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Żółć gęślą jaźń", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.376016332302243, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "b315278456c1ca7cf6e66a85f6afdfb854e152b242ca174886bc2e04c6de20aa", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_02_zolc\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"97ce2d1f83ec86467713ea74d9e0c8db02f10913ba1431ea5356ee09ae81b5a2\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:38:07.031922+00:00\", \"finished_at\": \"2026-10-21T17:38:29.409248+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.376016332302243, \"image\": \"./zimage_pl_02_zolc_1024x1024_12s_2026.png\", \"sha256\": \"b315278456c1ca7cf6e66a85f6afdfb854e152b242ca174886bc2e04c6de20aa\"}"} +{"file_name": "images/d1a73516022086d566e8.png", "image_id": "d1a73516022086d566e8", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_03_lodz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A red vintage railway destination plate on a dark blue train, natural weathering.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Łódź – Żyrardów\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Łódź – Żyrardów", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.350213784258813, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "8d4445972c6c50fd8c5312eefc7c3c958ab79cda52794e072097fe690223e2ac", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_03_lodz\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"12fb411985827fb1f29cd500311a1c11655b06bb4264956579579547b8b27782\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:38:29.409832+00:00\", \"finished_at\": \"2026-10-21T17:38:51.761346+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.350213784258813, \"image\": \"./zimage_pl_03_lodz_1024x1024_12s_2026.png\", \"sha256\": \"8d4445972c6c50fd8c5312eefc7c3c958ab79cda52794e072097fe690223e2ac\"}"} +{"file_name": "images/5030e09154776f58064f.png", "image_id": "5030e09154776f58064f", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_04_wazny", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A folded letterpress invitation on cream textured paper, realistic macro photograph.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Zażółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Zażółć gęślą jaźń", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.38124042795971, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "2791c82d52fcb7d52808536b9e258f96c2f62e08b152b2b5b318f42dd016b8ec", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_04_wazny\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e66e47fea697817f7ed9dc550118e94c943c53e9f15a1c16d33a6b746287572d\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:38:51.761927+00:00\", \"finished_at\": \"2026-10-21T17:39:14.144471+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.38124042795971, \"image\": \"./zimage_pl_04_wazny_1024x1024_12s_2026.png\", \"sha256\": \"2791c82d52fcb7d52808536b9e258f96c2f62e08b152b2b5b318f42dd016b8ec\"}"} +{"file_name": "images/193d74122e0ab01b9f60.png", "image_id": "193d74122e0ab01b9f60", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_05_sprzedaz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"Realistic modern storefront with black metal letters on cream marble, overcast outdoor street.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Świeże pączki\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Świeże pączki", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.38176469365135, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "6e9f3dbe9a8d2484af1f63c18bb3218fcf650a128f2232f80e355363fa4eff6f", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_05_sprzedaz\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"0d14212e6ec85499bfb2b49558558b1e3f649bc3d35bf2bfc2bc3decdf33ecd4\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:39:14.145079+00:00\", \"finished_at\": \"2026-10-21T17:39:36.528176+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.38176469365135, \"image\": \"./zimage_pl_05_sprzedaz_1024x1024_12s_2026.png\", \"sha256\": \"6e9f3dbe9a8d2484af1f63c18bb3218fcf650a128f2232f80e355363fa4eff6f\"}"} +{"file_name": "images/d69c77d8c6246320a34c.png", "image_id": "d69c77d8c6246320a34c", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_06_jezyk", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A handwritten memo on a study desk beside a mechanical pencil and a cup of tea.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Książę i księżniczka\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Książę i księżniczka", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.385016348212957, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "d844ea111e9513027b09013dec991327cfd25296bba8baa72704268ea9ec2a5c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_06_jezyk\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e0580c39685f00584f3e7a949191eb950c3e5220bc7121906052fd70993a1d85\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:39:36.528706+00:00\", \"finished_at\": \"2026-10-21T17:39:58.914947+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.385016348212957, \"image\": \"./zimage_pl_06_jezyk_1024x1024_12s_2026.png\", \"sha256\": \"d844ea111e9513027b09013dec991327cfd25296bba8baa72704268ea9ec2a5c\"}"} +{"file_name": "images/873b04252b874d6c22fe.png", "image_id": "873b04252b874d6c22fe", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_07_dwa_wiersze", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A square enamel noticeboard on a historic Kraków 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Entirely original character and setting, no existing franchise or copyrighted character.", "expected_text": null, "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 23.122746813111007, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "0c242b59a9c829f247ca3d5fadc031f16a136caf25b34830a65b910d4107624c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"style_01_anime_woman\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:44:02.983269+00:00\", \"finished_at\": \"2026-10-21T17:44:26.107221+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 23.122746813111007, \"image\": \"./zimage_style_01_anime_woman_1024x1024_12s_2026.png\", \"sha256\": \"0c242b59a9c829f247ca3d5fadc031f16a136caf25b34830a65b910d4107624c\"}"} +{"file_name": "images/5ad2ff406235d9a2f261.png", "image_id": "5ad2ff406235d9a2f261", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "style_02_river_bakery", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-end photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood facade, large glass windows with layered city reflections, intricate golden croissants, artisan breads in a display, elegant brass lamps, stone sidewalk with dappled tree shadows, realistic metal, glass, fabric and bread textures, rich dynamic range and sharp yet natural fine detail. Frontal slightly angled wide view, no logos and no extra printed or handwritten text beyond the main bakery sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"one beautifully letterspaced legible gold serif sign on the dark fascia above the glass storefront\",\"text\":\"RIVER BAKERY\",\"bbox\":[-380,-380,-200,380]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "RIVER BAKERY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 23.25855834176764, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "0608a341c6b619acecad25bf7250e9d5496f930a7a1f7b6e2cb46b54bd921a8e", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"style_02_river_bakery\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:44:26.107769+00:00\", \"finished_at\": \"2026-10-21T17:44:49.367730+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 23.25855834176764, \"image\": \"./zimage_style_02_river_bakery_1024x1024_12s_2026.png\", \"sha256\": \"0608a341c6b619acecad25bf7250e9d5496f930a7a1f7b6e2cb46b54bd921a8e\"}"} +{"file_name": "images/65140a916702aa6c5047.png", "image_id": "65140a916702aa6c5047", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_natural_paczki", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.1295323302038, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "5bbc141ed65eda2cd7e8a7c490448fc6b5d0019d52c2d1a1dc473ee1edb180c6", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_natural_paczki\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"2f2bd73b09b37eec803b6d3f9d88fa35dacb0c8d352f6888802bb49f4296aead\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:44:49.368362+00:00\", \"finished_at\": \"2026-10-21T17:45:11.499230+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.1295323302038, \"image\": \"./zimage_pl_natural_paczki_1024x1024_12s_2026.png\", \"sha256\": \"5bbc141ed65eda2cd7e8a7c490448fc6b5d0019d52c2d1a1dc473ee1edb180c6\"}"} +{"file_name": "images/9419c818986164b1f407.png", "image_id": "9419c818986164b1f407", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_menu_prices", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.177930642850697, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "8ab93a45e57b70a76f9f511bb084321006b3becd79e41520b6cb3dbefd5badbe", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_menu_prices\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:45:11.499813+00:00\", \"finished_at\": \"2026-10-21T17:45:33.678970+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.177930642850697, \"image\": \"./zimage_pl_menu_prices_1024x1024_12s_2026.png\", \"sha256\": \"8ab93a45e57b70a76f9f511bb084321006b3becd79e41520b6cb3dbefd5badbe\"}"} +{"file_name": "images/a77c482643e5f65c486c.png", "image_id": "a77c482643e5f65c486c", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 21.982038301881403, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "e2b5bdebc5531997777f90e461df83b0a51bdc3b7a0582915a40189f827d5b93", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_poster_multiline\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:45:33.679511+00:00\", \"finished_at\": \"2026-10-21T17:45:55.662635+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 21.982038301881403, \"image\": \"./zimage_pl_poster_multiline_1024x1024_12s_2026.png\", \"sha256\": \"e2b5bdebc5531997777f90e461df83b0a51bdc3b7a0582915a40189f827d5b93\"}"} +{"file_name": "images/5a43e093d68f3ead3433.png", "image_id": "5a43e093d68f3ead3433", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.164802191779017, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "def3a648251358eea6461e84d7f09f2702e9aac361e99e2efebd35776aef979c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"pl_long_sentence\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"42cdd9f49317e3a8a71484e31487bb412a61c0594d34d3e18900e94ca64b3478\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T17:45:55.663018+00:00\", \"finished_at\": \"2026-10-21T17:46:17.829563+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.164802191779017, \"image\": \"./zimage_pl_long_sentence_1024x1024_12s_2026.png\", \"sha256\": \"def3a648251358eea6461e84d7f09f2702e9aac361e99e2efebd35776aef979c\"}"} +{"file_name": "images/46073d99beaad8e537b8.png", "image_id": "46073d99beaad8e537b8", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 28.35384690295905, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "95f3c54de1c036adf198f67116f59ad627e0cff8cd8d3864e9042b9d72654822", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"bakery_plain_en\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T18:02:54.138572+00:00\", \"finished_at\": \"2026-10-21T18:03:22.497551+00:00\", \"first_in_process\": true, \"seconds_http_including_png\": 28.35384690295905, \"image\": \"./zimage_bakery_plain_en_1024x1024_12s_42.png\", \"sha256\": \"95f3c54de1c036adf198f67116f59ad627e0cff8cd8d3864e9042b9d72654822\"}"} +{"file_name": "images/59036a4295654c2e658d.png", "image_id": "59036a4295654c2e658d", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 23.07585178874433, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "285330d485e51c0f669072812c9b8a9c4a39f4d9e757b6faf0fb4e522be2cfd7", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"bakery_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T18:03:22.498227+00:00\", \"finished_at\": \"2026-10-21T18:03:45.575489+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 23.07585178874433, \"image\": \"./zimage_bakery_plain_pl_1024x1024_12s_42.png\", \"sha256\": \"285330d485e51c0f669072812c9b8a9c4a39f4d9e757b6faf0fb4e522be2cfd7\"}"} +{"file_name": "images/0a29802dfaa1fb04f193.png", "image_id": "0a29802dfaa1fb04f193", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.358173545915633, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "d0933fadb439cf0022cd19e277b0ab2ecff9ee698fda602554704bbad91814b7", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"paczki_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T18:03:45.576088+00:00\", \"finished_at\": \"2026-10-21T18:04:07.935400+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.358173545915633, \"image\": \"./zimage_paczki_plain_pl_1024x1024_12s_42.png\", \"sha256\": \"d0933fadb439cf0022cd19e277b0ab2ecff9ee698fda602554704bbad91814b7\"}"} +{"file_name": "images/a1d66d92427f228fc5ea.png", "image_id": "a1d66d92427f228fc5ea", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 42, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.373504771851003, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "2b155b3cad82171fb656df2d2a0f7ae8f2a138edef1d8031f0469fc9361b80c9", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"menu_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"ecb6b45818e51a94009f5e96927974aec0132a3530b33022398ef29a6e179c3f\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 42, \"started_at\": \"2026-10-21T18:04:07.935935+00:00\", \"finished_at\": \"2026-10-21T18:04:30.310575+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.373504771851003, \"image\": \"./zimage_menu_plain_pl_1024x1024_12s_42.png\", \"sha256\": \"2b155b3cad82171fb656df2d2a0f7ae8f2a138edef1d8031f0469fc9361b80c9\"}"} +{"file_name": "images/39e5d7dd0f18d8b90df4.png", "image_id": "39e5d7dd0f18d8b90df4", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.202409389894456, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "3d29e3b057a6eb277c90bc5baa80160072b5286abf0259621c7b3d9d515d1af9", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"bakery_plain_en\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T18:04:30.311103+00:00\", \"finished_at\": \"2026-10-21T18:04:52.514797+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.202409389894456, \"image\": \"./zimage_bakery_plain_en_1024x1024_12s_2026.png\", \"sha256\": \"3d29e3b057a6eb277c90bc5baa80160072b5286abf0259621c7b3d9d515d1af9\"}"} +{"file_name": "images/8d9b3b9365f3569514a0.png", "image_id": "8d9b3b9365f3569514a0", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 23.012225835118443, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "38e267e8c4a3e5d692b281208a7790a88df9fe65d4b58eddf490829b44c6f13a", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"bakery_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T18:04:52.515390+00:00\", \"finished_at\": \"2026-10-21T18:05:15.528993+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 23.012225835118443, \"image\": \"./zimage_bakery_plain_pl_1024x1024_12s_2026.png\", \"sha256\": \"38e267e8c4a3e5d692b281208a7790a88df9fe65d4b58eddf490829b44c6f13a\"}"} +{"file_name": "images/54334a4c59b0377176b5.png", "image_id": "54334a4c59b0377176b5", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.33967831498012, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "0a2c1e62003e4e000ce0347ddab55e52c0cd45e012df92ead908aad45e789fb3", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"paczki_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T18:05:15.529603+00:00\", \"finished_at\": \"2026-10-21T18:05:37.870423+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.33967831498012, \"image\": \"./zimage_paczki_plain_pl_1024x1024_12s_2026.png\", \"sha256\": \"0a2c1e62003e4e000ce0347ddab55e52c0cd45e012df92ead908aad45e789fb3\"}"} +{"file_name": "images/7bf3e217666e06af4cfb.png", "image_id": "7bf3e217666e06af4cfb", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "Z-Image-Turbo", "variant": "Z-Image-Turbo", "seed": 2026, "steps": 12, "cfg": 0, "mode": "production", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 22.301215352024883, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "HTTP + Qwen + generation + PNG", "prompt_encode_seconds": null, "diffusion_seconds": null, "decode_seconds": null, "png_seconds": null, "upscale_inference_seconds": null, "peak_allocated_gib": null, "peak_reserved_gib": null, "gpu": null, "torch": null, "vae_dtype": null, "encoder": null, "conditioning_sha256": null, "image_sha256": "b074f3fec731aec53ecf28db1bfd3bf815225d690cd1517ad2d27a3a72a08d5b", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"status\": \"ok\", \"backend\": \"production Z-Image-Turbo\", \"case\": \"menu_plain_pl\", \"variant\": \"Z-Image-Turbo\", \"mode\": \"production\", \"prompt_sha256\": \"ecb6b45818e51a94009f5e96927974aec0132a3530b33022398ef29a6e179c3f\", \"width\": 1024, \"height\": 1024, \"steps\": 12, \"cfg\": 0, \"seed\": 2026, \"started_at\": \"2026-10-21T18:05:37.870954+00:00\", \"finished_at\": \"2026-10-21T18:06:00.174117+00:00\", \"first_in_process\": false, \"seconds_http_including_png\": 22.301215352024883, \"image\": \"./zimage_menu_plain_pl_1024x1024_12s_2026.png\", \"sha256\": \"b074f3fec731aec53ecf28db1bfd3bf815225d690cd1517ad2d27a3a72a08d5b\"}"} +{"file_name": "images/15ea736744692742c046.png", "image_id": "15ea736744692742c046", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "style_02_river_bakery", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A high-end photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood facade, large glass windows with layered city reflections, intricate golden croissants, artisan breads in a display, elegant brass lamps, stone sidewalk with dappled tree shadows, realistic metal, glass, fabric and bread textures, rich dynamic range and sharp yet natural fine detail. Frontal slightly angled wide view, no logos and no extra printed or handwritten text beyond the main bakery sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"one beautifully letterspaced legible gold serif sign on the dark fascia above the glass storefront\",\"text\":\"RIVER BAKERY\",\"bbox\":[-380,-380,-200,380]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 151.70056385966018, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.1287592169828713, "diffusion_seconds": 150.8596268859692, "decode_seconds": 0.624524689745158, "png_seconds": 0.20334647316485643, "upscale_inference_seconds": null, "peak_allocated_gib": 12.544709205627441, "peak_reserved_gib": 14.595703125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "3f811a06248f65e2ad57ab5c30bb52fd4146e1cc3a5e946ab798700602ee2b23", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"bfloat16\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.914226220920682, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_02_river_bakery\", \"started_at\": \"2026-10-21T17:55:06.026946+00:00\", \"finished_at\": \"2026-10-21T17:57:37.727509+00:00\", \"prompt_sha256\": \"a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 1.1287592169828713, \"seconds_inference\": 151.49721682583913, \"diffusion_seconds\": 150.8596268859692, \"decode_seconds\": 0.624524689745158, \"png_seconds\": 0.20334647316485643, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 151.70056385966018, \"peak_allocated_gib\": 12.544709205627441, \"peak_reserved_gib\": 14.595703125, \"actual_steps\": 50, \"image\": \"./noise-control/bf16-original_eager-sft-float32-noisebfloat16-torch2.10.0-conda3cd376f_style_02_river_bakery_1024x1024_50s_42_0.png\", \"image_sha256\": \"3f811a06248f65e2ad57ab5c30bb52fd4146e1cc3a5e946ab798700602ee2b23\"}"} +{"file_name": "images/b8d8ada53494cfe20f4a.png", "image_id": "b8d8ada53494cfe20f4a", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "style_01_anime_woman", "prompt": "An original, high-quality anime illustration, cinematic medium portrait of an adult young woman aged 24 with expressive violet eyes and long dark brown hair flowing naturally in the evening breeze, detailed individual hair strands and delicate accessories, wearing a layered fashionable dark blue jacket and light blouse. She turns toward the viewer with a subtle friendly smile on a bustling lantern-lit city street at blue hour, intricate background architecture, neon reflections on wet stone paving, shallow depth, natural balanced anatomy and hands, exquisite clean line art and controlled cel shading, rich soft gradients, highly detailed face, fabrics, light and shadows, vivid but tasteful color palette. No text, no signs with lettering, no logos, no watermarks. 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Frontal slightly angled wide view, no logos and no extra printed or handwritten text beyond the main bakery sign.\"},\"items\":[{\"label\":\"text\",\"caption\":\"one beautifully letterspaced legible gold serif sign on the dark fascia above the glass storefront\",\"text\":\"RIVER BAKERY\",\"bbox\":[-380,-380,-200,380]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "fp8w8a8-tensor-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 74.16722723143175, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.1287592169828713, "diffusion_seconds": 73.42454627342522, "decode_seconds": 0.5319713726639748, "png_seconds": 0.20471227494999766, "upscale_inference_seconds": null, "peak_allocated_gib": 8.5360746383667, "peak_reserved_gib": 11.16015625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "42247005a352ac635d39c731c8e3c748912a4b3fc300fbb5dcb8606cfdb29c39", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 22.84, \"SSIM vs BF16\": 0.871386, \"RGB MAE vs BF16\": 10.3671}", "parameters_json": "{\"variant\": \"fp8w8a8-tensor-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.275649898685515, \"linear_weight_types\": {\"Parameter\": 41, \"LinearActivationQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.459343433380127, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_02_river_bakery\", \"started_at\": \"2026-10-21T19:38:37.356927+00:00\", \"finished_at\": \"2026-10-21T19:39:51.524153+00:00\", \"prompt_sha256\": \"a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 1.1287592169828713, \"seconds_inference\": 73.96251442516223, \"diffusion_seconds\": 73.42454627342522, \"decode_seconds\": 0.5319713726639748, \"png_seconds\": 0.20471227494999766, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 74.16722723143175, \"peak_allocated_gib\": 8.5360746383667, \"peak_reserved_gib\": 11.16015625, \"actual_steps\": 50, \"image\": \"./results/fp8w8a8-tensor-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_style_02_river_bakery_1024x1024_50s_42_0.png\", \"image_sha256\": \"42247005a352ac635d39c731c8e3c748912a4b3fc300fbb5dcb8606cfdb29c39\"}"} +{"file_name": "images/e34bd28bbcf0d75ca14a.png", "image_id": "e34bd28bbcf0d75ca14a", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.761974163353443, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6257610525935888, "diffusion_seconds": 9.947873008437455, "decode_seconds": 0.5855379067361355, "png_seconds": 0.21536681381985545, "upscale_inference_seconds": null, "peak_allocated_gib": 9.705788135528564, "peak_reserved_gib": 12.9609375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "89a5e7b16c7c6228f168bcd231f01e655ed7def5452f8e60c8482b200c0b28b5", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 3.6357757709920406, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_en\", \"started_at\": \"2026-10-21T19:40:29.080457+00:00\", \"finished_at\": \"2026-10-21T19:40:39.842429+00:00\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 0.6257610525935888, \"seconds_inference\": 10.546606798190624, \"diffusion_seconds\": 9.947873008437455, \"decode_seconds\": 0.5855379067361355, \"png_seconds\": 0.21536681381985545, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.761974163353443, \"peak_allocated_gib\": 9.705788135528564, \"peak_reserved_gib\": 12.9609375, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_bakery_plain_en_1024x1024_4s_42_0.png\", \"image_sha256\": \"89a5e7b16c7c6228f168bcd231f01e655ed7def5452f8e60c8482b200c0b28b5\"}"} +{"file_name": "images/6201fedb6e8203e8676f.png", "image_id": "6201fedb6e8203e8676f", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.5692705437541, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.8079748647287488, "diffusion_seconds": 9.839690212160349, "decode_seconds": 0.5310314879752696, "png_seconds": 0.19245223701000214, "upscale_inference_seconds": null, "peak_allocated_gib": 9.706398487091064, "peak_reserved_gib": 12.962890625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "4dee739eb79782791b12d8b5987bc00540a2ae0eea7a4ae73b62cadcc3b780de", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 3.6357757709920406, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_pl\", \"started_at\": \"2026-10-21T19:40:39.956268+00:00\", \"finished_at\": \"2026-10-21T19:40:50.525537+00:00\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.8079748647287488, \"seconds_inference\": 10.37681773584336, \"diffusion_seconds\": 9.839690212160349, \"decode_seconds\": 0.5310314879752696, \"png_seconds\": 0.19245223701000214, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.5692705437541, \"peak_allocated_gib\": 9.706398487091064, \"peak_reserved_gib\": 12.962890625, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_bakery_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"4dee739eb79782791b12d8b5987bc00540a2ae0eea7a4ae73b62cadcc3b780de\"}"} +{"file_name": "images/a55af1d9259cd07aead7.png", "image_id": "a55af1d9259cd07aead7", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.548572683241218, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7579642506316304, "diffusion_seconds": 9.830372367985547, "decode_seconds": 0.5311868251301348, "png_seconds": 0.18104050494730473, "upscale_inference_seconds": null, "peak_allocated_gib": 9.70624589920044, "peak_reserved_gib": 12.962890625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "66d05e20fcd911eb2e681c34f396e558ea7910820eb953ac34308ba632244976", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 3.6357757709920406, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"paczki_plain_pl\", \"started_at\": \"2026-10-21T19:40:50.629549+00:00\", \"finished_at\": \"2026-10-21T19:41:01.178120+00:00\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7579642506316304, \"seconds_inference\": 10.367531817406416, \"diffusion_seconds\": 9.830372367985547, \"decode_seconds\": 0.5311868251301348, \"png_seconds\": 0.18104050494730473, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.548572683241218, \"peak_allocated_gib\": 9.70624589920044, \"peak_reserved_gib\": 12.962890625, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_paczki_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"66d05e20fcd911eb2e681c34f396e558ea7910820eb953ac34308ba632244976\"}"} +{"file_name": "images/0f7580288dd699d20177.png", "image_id": "0f7580288dd699d20177", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.599347915966064, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7399788070470095, "diffusion_seconds": 9.83110329695046, "decode_seconds": 0.5314130070619285, "png_seconds": 0.23093775613233447, "upscale_inference_seconds": null, "peak_allocated_gib": 9.70624589920044, "peak_reserved_gib": 12.962890625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "6f9d4c209602b5a378382bc0fa8911c1427a1c3f55ccb4b9762b4c03ed95a9db", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 3.6357757709920406, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"menu_plain_pl\", \"started_at\": \"2026-10-21T19:41:01.276585+00:00\", \"finished_at\": \"2026-10-21T19:41:11.875932+00:00\", \"prompt_sha256\": \"ecb6b45818e51a94009f5e96927974aec0132a3530b33022398ef29a6e179c3f\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7399788070470095, \"seconds_inference\": 10.368409669958055, \"diffusion_seconds\": 9.83110329695046, \"decode_seconds\": 0.5314130070619285, \"png_seconds\": 0.23093775613233447, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.599347915966064, \"peak_allocated_gib\": 9.70624589920044, \"peak_reserved_gib\": 12.962890625, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_menu_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"6f9d4c209602b5a378382bc0fa8911c1427a1c3f55ccb4b9762b4c03ed95a9db\"}"} +{"file_name": "images/0a6c8f673e1b778df329.png", "image_id": "0a6c8f673e1b778df329", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 109.62557239318267, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6257610525935888, "diffusion_seconds": 108.77365472819656, "decode_seconds": 0.6162898750044405, "png_seconds": 0.22211169265210629, "upscale_inference_seconds": null, "peak_allocated_gib": 8.53798770904541, "peak_reserved_gib": 11.19921875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "82a214747266ac0d3ff36e0baba95b7fa939879118caa59d00925539750eeb3c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2197745363228023, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_en\", \"started_at\": \"2026-10-21T19:41:21.843235+00:00\", \"finished_at\": \"2026-10-21T19:43:11.468805+00:00\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 0.6257610525935888, \"seconds_inference\": 109.40346022928134, \"diffusion_seconds\": 108.77365472819656, \"decode_seconds\": 0.6162898750044405, \"png_seconds\": 0.22211169265210629, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 109.62557239318267, \"peak_allocated_gib\": 8.53798770904541, \"peak_reserved_gib\": 11.19921875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-cond070bf0e9_bakery_plain_en_1024x1024_50s_42_0.png\", \"image_sha256\": \"82a214747266ac0d3ff36e0baba95b7fa939879118caa59d00925539750eeb3c\"}"} +{"file_name": "images/7c5b8e0ef5bc39b08aad.png", "image_id": "7c5b8e0ef5bc39b08aad", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.24160561524332, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.8079748647287488, "diffusion_seconds": 107.49000638816506, "decode_seconds": 0.5315272980369627, "png_seconds": 0.21399231208488345, "upscale_inference_seconds": null, "peak_allocated_gib": 8.53859806060791, "peak_reserved_gib": 11.201171875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "3f595c4c3ec81e3f7a8f2f0ac79eb6fac32fefe090f93b6b4f1f2fb4b10c1185", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2197745363228023, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_pl\", \"started_at\": \"2026-10-21T19:43:11.607117+00:00\", \"finished_at\": \"2026-10-21T19:44:59.848723+00:00\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.8079748647287488, \"seconds_inference\": 108.02761280210689, \"diffusion_seconds\": 107.49000638816506, \"decode_seconds\": 0.5315272980369627, \"png_seconds\": 0.21399231208488345, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 108.24160561524332, \"peak_allocated_gib\": 8.53859806060791, \"peak_reserved_gib\": 11.201171875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-cond070bf0e9_bakery_plain_pl_1024x1024_50s_42_0.png\", \"image_sha256\": \"3f595c4c3ec81e3f7a8f2f0ac79eb6fac32fefe090f93b6b4f1f2fb4b10c1185\"}"} +{"file_name": "images/bb32bd86bde79d5ee3b2.png", "image_id": "bb32bd86bde79d5ee3b2", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.2352042091079, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7579642506316304, "diffusion_seconds": 107.47679960215464, "decode_seconds": 0.5314076449722052, "png_seconds": 0.22079619579017162, "upscale_inference_seconds": null, "peak_allocated_gib": 8.538445472717285, "peak_reserved_gib": 11.201171875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "c2b9b9717c936e42ed6c9821a47cae83d6bdbbaf0703d2cea0873bfbf8f39ded", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2197745363228023, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"paczki_plain_pl\", \"started_at\": \"2026-10-21T19:44:59.985353+00:00\", \"finished_at\": \"2026-10-21T19:46:48.220553+00:00\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7579642506316304, \"seconds_inference\": 108.01440749224275, \"diffusion_seconds\": 107.47679960215464, \"decode_seconds\": 0.5314076449722052, \"png_seconds\": 0.22079619579017162, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 108.2352042091079, \"peak_allocated_gib\": 8.538445472717285, \"peak_reserved_gib\": 11.201171875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-cond070bf0e9_paczki_plain_pl_1024x1024_50s_42_0.png\", \"image_sha256\": \"c2b9b9717c936e42ed6c9821a47cae83d6bdbbaf0703d2cea0873bfbf8f39ded\"}"} +{"file_name": "images/3c97f74e19a2c67bfc3c.png", "image_id": "3c97f74e19a2c67bfc3c", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.25033224467188, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7399788070470095, "diffusion_seconds": 107.48749607568607, "decode_seconds": 0.5313338031992316, "png_seconds": 0.22560054436326027, "upscale_inference_seconds": null, "peak_allocated_gib": 8.538445472717285, "peak_reserved_gib": 11.201171875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "c2cf33b9b80803ee3d667536a6eb92ef540e7739631cf4cb55f40cb235fb73b7", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2197745363228023, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"menu_plain_pl\", \"started_at\": \"2026-10-21T19:46:48.370675+00:00\", \"finished_at\": \"2026-10-21T19:48:36.621009+00:00\", \"prompt_sha256\": \"ecb6b45818e51a94009f5e96927974aec0132a3530b33022398ef29a6e179c3f\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7399788070470095, \"seconds_inference\": 108.02473115967587, \"diffusion_seconds\": 107.48749607568607, \"decode_seconds\": 0.5313338031992316, \"png_seconds\": 0.22560054436326027, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 108.25033224467188, \"peak_allocated_gib\": 8.538445472717285, \"peak_reserved_gib\": 11.201171875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-cond070bf0e9_menu_plain_pl_1024x1024_50s_42_0.png\", \"image_sha256\": \"c2cf33b9b80803ee3d667536a6eb92ef540e7739631cf4cb55f40cb235fb73b7\"}"} +{"file_name": "images/67a9200c6d9e990140b8.png", "image_id": "67a9200c6d9e990140b8", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.341034510172904, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6257610525935888, "diffusion_seconds": 9.531880219001323, "decode_seconds": 0.5855325311422348, "png_seconds": 0.20990698505192995, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712528705596924, "peak_reserved_gib": 12.966796875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "c5febd1a534a533f99a83392b9ee0c8a94952d027474b45e414a783a926d9c32", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2173488070257008, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_en\", \"started_at\": \"2026-10-21T19:48:50.884749+00:00\", \"finished_at\": \"2026-10-21T19:49:01.225788+00:00\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 0.6257610525935888, \"seconds_inference\": 10.131127044092864, \"diffusion_seconds\": 9.531880219001323, \"decode_seconds\": 0.5855325311422348, \"png_seconds\": 0.20990698505192995, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.341034510172904, \"peak_allocated_gib\": 9.712528705596924, \"peak_reserved_gib\": 12.966796875, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_bakery_plain_en_1024x1024_4s_42_0.png\", \"image_sha256\": \"c5febd1a534a533f99a83392b9ee0c8a94952d027474b45e414a783a926d9c32\"}"} +{"file_name": "images/f81f92070b2a561169f0.png", "image_id": "f81f92070b2a561169f0", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.148942170199007, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.8079748647287488, "diffusion_seconds": 9.42352021113038, "decode_seconds": 0.531398911960423, "png_seconds": 0.18797767395153642, "upscale_inference_seconds": null, "peak_allocated_gib": 9.713139057159424, "peak_reserved_gib": 12.970703125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "405bf8f5a4cd7626310f4f218001cce90629046f9ffd51f17a780be32083db34", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2173488070257008, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_pl\", \"started_at\": \"2026-10-21T19:49:01.324718+00:00\", \"finished_at\": \"2026-10-21T19:49:11.473654+00:00\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.8079748647287488, \"seconds_inference\": 9.96096397517249, \"diffusion_seconds\": 9.42352021113038, \"decode_seconds\": 0.531398911960423, \"png_seconds\": 0.18797767395153642, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.148942170199007, \"peak_allocated_gib\": 9.713139057159424, \"peak_reserved_gib\": 12.970703125, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_bakery_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"405bf8f5a4cd7626310f4f218001cce90629046f9ffd51f17a780be32083db34\"}"} +{"file_name": "images/fcfafd17c078a0b61bb4.png", "image_id": "fcfafd17c078a0b61bb4", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.134595714975148, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7579642506316304, "diffusion_seconds": 9.412010374013335, "decode_seconds": 0.5312560056336224, "png_seconds": 0.18543383479118347, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712986469268799, "peak_reserved_gib": 12.970703125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "7f5cdbfc7ee78fa812b0853d0a74ba487531e94e5624e124a08fd04e12cebd6a", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2173488070257008, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"paczki_plain_pl\", \"started_at\": \"2026-10-21T19:49:11.578866+00:00\", \"finished_at\": \"2026-10-21T19:49:21.713457+00:00\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7579642506316304, \"seconds_inference\": 9.949161409866065, \"diffusion_seconds\": 9.412010374013335, \"decode_seconds\": 0.5312560056336224, \"png_seconds\": 0.18543383479118347, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.134595714975148, \"peak_allocated_gib\": 9.712986469268799, \"peak_reserved_gib\": 12.970703125, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_paczki_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"7f5cdbfc7ee78fa812b0853d0a74ba487531e94e5624e124a08fd04e12cebd6a\"}"} +{"file_name": "images/90fec5fa1b946ee7f2b3.png", "image_id": "90fec5fa1b946ee7f2b3", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.1756616611965, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7399788070470095, "diffusion_seconds": 9.412339720875025, "decode_seconds": 0.5313173229806125, "png_seconds": 0.22602387610822916, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712986469268799, "peak_reserved_gib": 12.970703125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "baada8d1e7ed6be45d4ee0f0ffe1543a3c23b83fe8683fa2627adc7efca936f5", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2173488070257008, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"menu_plain_pl\", \"started_at\": \"2026-10-21T19:49:21.816034+00:00\", \"finished_at\": \"2026-10-21T19:49:31.991689+00:00\", \"prompt_sha256\": \"ecb6b45818e51a94009f5e96927974aec0132a3530b33022398ef29a6e179c3f\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7399788070470095, \"seconds_inference\": 9.949636722914875, \"diffusion_seconds\": 9.412339720875025, \"decode_seconds\": 0.5313173229806125, \"png_seconds\": 0.22602387610822916, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 10.1756616611965, \"peak_allocated_gib\": 9.712986469268799, \"peak_reserved_gib\": 12.970703125, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-cond070bf0e9_menu_plain_pl_1024x1024_4s_42_0.png\", \"image_sha256\": \"baada8d1e7ed6be45d4ee0f0ffe1543a3c23b83fe8683fa2627adc7efca936f5\"}"} +{"file_name": "images/d91470cb58c357ca9243.png", "image_id": "d91470cb58c357ca9243", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_en", "prompt": "A photorealistic editorial photograph of a boutique European bakery storefront in warm daylight. Charcoal painted wood, large glass windows with city reflections, golden croissants and artisan breads, brass lamps, stone sidewalk and tree shadows. One large gold serif sign must read exactly RIVER BAKERY. Spell every letter correctly. No other text.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.67517104791477, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6257610525935888, "diffusion_seconds": 156.82692517479882, "decode_seconds": 0.6170657062903047, "png_seconds": 0.2176875602453947, "upscale_inference_seconds": null, "peak_allocated_gib": 8.54472827911377, "peak_reserved_gib": 11.5, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "3e98cbb8e6f69b698857321942db76ae9718f0c4abadd70788fe2df753cedc75", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2158046341501176, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_en\", \"started_at\": \"2026-10-21T19:49:42.302832+00:00\", \"finished_at\": \"2026-10-21T19:52:19.978004+00:00\", \"prompt_sha256\": \"44422f55b9c34a0f1aba23f6619d6d912a9251b84f3af2bc6393d8f58aba820f\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 0.6257610525935888, \"seconds_inference\": 157.45748299686238, \"diffusion_seconds\": 156.82692517479882, \"decode_seconds\": 0.6170657062903047, \"png_seconds\": 0.2176875602453947, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 157.67517104791477, \"peak_allocated_gib\": 8.54472827911377, \"peak_reserved_gib\": 11.5, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-cond070bf0e9_bakery_plain_en_1024x1024_50s_42_0.png\", \"image_sha256\": \"3e98cbb8e6f69b698857321942db76ae9718f0c4abadd70788fe2df753cedc75\"}"} +{"file_name": "images/3b9fed0a9430acf2615e.png", "image_id": "3b9fed0a9430acf2615e", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "bakery_plain_pl", "prompt": "Fotorealistyczne zdjęcie eleganckiej europejskiej piekarni w ciepłym świetle dnia. Ciemna drewniana fasada, duże szklane witryny z odbiciami miasta, złociste rogaliki i chleby, mosiężne lampy, kamienny chodnik i cienie drzew. Duży złoty szyld ma zawierać dokładnie napis: RIVER BAKERY. Zachowaj wszystkie litery i spację. Bez innych napisów.", "expected_text": "RIVER BAKERY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.7253199480474, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.8079748647287488, "diffusion_seconds": 156.97642630012706, "decode_seconds": 0.5315569108352065, "png_seconds": 0.21126375114545226, "upscale_inference_seconds": null, "peak_allocated_gib": 8.54533863067627, "peak_reserved_gib": 11.50390625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "dbb71c5008b1c6f6b1e1f7b9caba9d06bb1885c8a0323d3b3e08e87651490a58", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2158046341501176, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"bakery_plain_pl\", \"started_at\": \"2026-10-21T19:52:20.082145+00:00\", \"finished_at\": \"2026-10-21T19:54:57.807463+00:00\", \"prompt_sha256\": \"c01e54a6d53fc18ff87f0ff3d1d074c894e378e512037fa8be6f5c420ec8df49\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.8079748647287488, \"seconds_inference\": 157.5140557559207, \"diffusion_seconds\": 156.97642630012706, \"decode_seconds\": 0.5315569108352065, \"png_seconds\": 0.21126375114545226, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 157.7253199480474, \"peak_allocated_gib\": 8.54533863067627, \"peak_reserved_gib\": 11.50390625, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-cond070bf0e9_bakery_plain_pl_1024x1024_50s_42_0.png\", \"image_sha256\": \"dbb71c5008b1c6f6b1e1f7b9caba9d06bb1885c8a0323d3b3e08e87651490a58\"}"} +{"file_name": "images/5174d28f118e7245ba35.png", "image_id": "5174d28f118e7245ba35", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "paczki_plain_pl", "prompt": "Fotorealistyczne zdjęcie polskiej cukierni w miękkim porannym świetle. Nad witryną jeden wyraźny szyld z dokładnym napisem: ŚWIEŻE PĄCZKI. Zachowaj polskie znaki Ś, Ż, Ą. Ciemne drewno, złote litery szeryfowe, pączki za szkłem i realistyczne odbicia. Bez dodatkowych napisów.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.64749795990065, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7579642506316304, "diffusion_seconds": 156.89106275094673, "decode_seconds": 0.5313636809587479, "png_seconds": 0.21917340205982327, "upscale_inference_seconds": null, "peak_allocated_gib": 8.545186042785645, "peak_reserved_gib": 11.50390625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "93af98335cf7184a5b4ac267e3fea15c5a1b00a8482d9f09b999b85d597f6bb4", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2158046341501176, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"paczki_plain_pl\", \"started_at\": \"2026-10-21T19:54:57.904093+00:00\", \"finished_at\": \"2026-10-21T19:57:35.551589+00:00\", \"prompt_sha256\": \"e11132e5e89dab971651578758ab516d98e8a89b3af6b992e719ff02409af22c\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.7579642506316304, \"seconds_inference\": 157.4283240167424, \"diffusion_seconds\": 156.89106275094673, \"decode_seconds\": 0.5313636809587479, \"png_seconds\": 0.21917340205982327, \"negative_encode_seconds_cold\": 0.7983906040899456, \"seconds_including_png\": 157.64749795990065, \"peak_allocated_gib\": 8.545186042785645, \"peak_reserved_gib\": 11.50390625, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-cond070bf0e9_paczki_plain_pl_1024x1024_50s_42_0.png\", \"image_sha256\": \"93af98335cf7184a5b4ac267e3fea15c5a1b00a8482d9f09b999b85d597f6bb4\"}"} +{"file_name": "images/4c69d5620413a2654e64.png", "image_id": "4c69d5620413a2654e64", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "menu_plain_pl", "prompt": "Zdjęcie tablicy z menu polskiej kawiarni, widok na wprost, prosta jasna ściana i czytelne kredowe litery. Na tablicy mają być dokładnie trzy wiersze:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nZachowaj polskie litery, przecinki w cenach i odstępy. Bez dodatkowych napisów.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.66579827899113, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7399788070470095, "diffusion_seconds": 156.8933032574132, "decode_seconds": 0.5313488887622952, "png_seconds": 0.23520405683666468, "upscale_inference_seconds": null, "peak_allocated_gib": 8.545186042785645, "peak_reserved_gib": 11.50390625, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "070bf0e95b0553fc810758f4bef8ece72e8e16b801b953e1ca61df63c028eea6", "image_sha256": "fb7a71be0c486ca84034ea4a7fca7d404cd5ef2b37e75ce98ef46d4f2773ecad", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; 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Entirely original character and setting, no existing franchise or copyrighted character.", "expected_text": null, "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.074846144299954, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.022591732442379, "diffusion_seconds": 9.339313051197678, "decode_seconds": 0.5312522291205823, "png_seconds": 0.1982871606014669, "upscale_inference_seconds": null, "peak_allocated_gib": 13.675293445587158, "peak_reserved_gib": 14.630859375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "6b7040ea72d4f74dfd1825dd5581ba38af1721f42f808f3c457c12ad07ae3e24", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 14.989461263641715, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_01_anime_woman\", \"started_at\": \"2026-10-21T20:10:08.704256+00:00\", \"finished_at\": \"2026-10-21T20:10:18.779101+00:00\", \"prompt_sha256\": \"0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 1.022591732442379, \"seconds_inference\": 9.876558472402394, \"diffusion_seconds\": 9.339313051197678, \"decode_seconds\": 0.5312522291205823, \"png_seconds\": 0.1982871606014669, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.074846144299954, \"peak_allocated_gib\": 13.675293445587158, \"peak_reserved_gib\": 14.630859375, \"actual_steps\": 4, \"image\": \"./results/bf16-original_eager-student-float32-torch2.10.0-conda3cd376f_style_01_anime_woman_1024x1024_4s_42_0.png\", \"image_sha256\": \"6b7040ea72d4f74dfd1825dd5581ba38af1721f42f808f3c457c12ad07ae3e24\"}"} +{"file_name": "images/bfc2cd7eb5a5b37f3b6c.png", "image_id": "bfc2cd7eb5a5b37f3b6c", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_natural_paczki", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 9.70830394141376, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.5981574859470129, "diffusion_seconds": 8.967605220153928, "decode_seconds": 0.5314369020052254, "png_seconds": 0.20304281217977405, "upscale_inference_seconds": null, "peak_allocated_gib": 13.67433214187622, "peak_reserved_gib": 14.630859375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "6c5bee6d5538c68d73e437b3cc23391bba36853e5487b533b109732ea003da37", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 14.989461263641715, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_natural_paczki\", \"started_at\": \"2026-10-21T20:10:18.877849+00:00\", \"finished_at\": \"2026-10-21T20:10:28.586151+00:00\", \"prompt_sha256\": \"2f2bd73b09b37eec803b6d3f9d88fa35dacb0c8d352f6888802bb49f4296aead\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.5981574859470129, \"seconds_inference\": 9.505260608159006, \"diffusion_seconds\": 8.967605220153928, \"decode_seconds\": 0.5314369020052254, \"png_seconds\": 0.20304281217977405, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 9.70830394141376, \"peak_allocated_gib\": 13.67433214187622, \"peak_reserved_gib\": 14.630859375, \"actual_steps\": 4, \"image\": \"./results/bf16-original_eager-student-float32-torch2.10.0-conda3cd376f_pl_natural_paczki_1024x1024_4s_42_0.png\", \"image_sha256\": \"6c5bee6d5538c68d73e437b3cc23391bba36853e5487b533b109732ea003da37\"}"} +{"file_name": "images/31d3d89bb44ef88c7a9e.png", "image_id": "31d3d89bb44ef88c7a9e", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_menu_prices", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 9.693823898676783, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 8.976470989640802, "decode_seconds": 0.5313262389972806, "png_seconds": 0.18011073302477598, "upscale_inference_seconds": null, "peak_allocated_gib": 13.674347400665283, "peak_reserved_gib": 14.630859375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "c70586aeb0959b45c45895a6a631869771bd7d6fe94c20fa3cf08656a29f7ed2", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 14.989461263641715, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T20:10:28.682556+00:00\", \"finished_at\": \"2026-10-21T20:10:38.376378+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 9.51371271489188, \"diffusion_seconds\": 8.976470989640802, \"decode_seconds\": 0.5313262389972806, \"png_seconds\": 0.18011073302477598, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 9.693823898676783, \"peak_allocated_gib\": 13.674347400665283, \"peak_reserved_gib\": 14.630859375, \"actual_steps\": 4, \"image\": \"./results/bf16-original_eager-student-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_4s_42_0.png\", \"image_sha256\": \"c70586aeb0959b45c45895a6a631869771bd7d6fe94c20fa3cf08656a29f7ed2\"}"} +{"file_name": "images/1301c1c9144c7103a6df.png", "image_id": "1301c1c9144c7103a6df", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 9.696392007637769, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 8.98463911190629, "decode_seconds": 0.5313182878307998, "png_seconds": 0.1743259271606803, "upscale_inference_seconds": null, "peak_allocated_gib": 13.674499988555908, "peak_reserved_gib": 14.630859375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "c3ba658bd96552f10936961038c8137c74904c43a44dbd79a9714792a7a8febc", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 14.989461263641715, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T20:10:38.471689+00:00\", \"finished_at\": \"2026-10-21T20:10:48.168079+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 9.522065499797463, \"diffusion_seconds\": 8.98463911190629, \"decode_seconds\": 0.5313182878307998, \"png_seconds\": 0.1743259271606803, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 9.696392007637769, \"peak_allocated_gib\": 13.674499988555908, \"peak_reserved_gib\": 14.630859375, \"actual_steps\": 4, \"image\": \"./results/bf16-original_eager-student-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_4s_42_0.png\", \"image_sha256\": \"c3ba658bd96552f10936961038c8137c74904c43a44dbd79a9714792a7a8febc\"}"} +{"file_name": "images/d65282ddef1dcf7a150d.png", "image_id": "d65282ddef1dcf7a150d", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 9.7002736129798, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.629698131699115, "diffusion_seconds": 8.980219651944935, "decode_seconds": 0.531319497153163, "png_seconds": 0.18273987900465727, "upscale_inference_seconds": null, "peak_allocated_gib": 13.674438953399658, "peak_reserved_gib": 14.630859375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "9b72fd36ba6b750aadc7e75ea2bc289b3b1dcd331ab2fbf19c2d3942d195cbef", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; 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Entirely original character and setting, no existing franchise or copyrighted character.", "expected_text": null, "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.43966225581244, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.022591732442379, "diffusion_seconds": 107.70518162799999, "decode_seconds": 0.5314825600944459, "png_seconds": 0.19698648201301694, "upscale_inference_seconds": null, "peak_allocated_gib": 12.54476261138916, "peak_reserved_gib": 15.01953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "c2d29c0ed15f0a9f94883179c9e2e863b603872a2d5b087c1165525aa1fdde48", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.810059119015932, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_01_anime_woman\", \"started_at\": \"2026-10-21T20:33:57.978455+00:00\", \"finished_at\": \"2026-10-21T20:35:46.418119+00:00\", \"prompt_sha256\": \"0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 1.022591732442379, \"seconds_inference\": 108.24267509300262, \"diffusion_seconds\": 107.70518162799999, \"decode_seconds\": 0.5314825600944459, \"png_seconds\": 0.19698648201301694, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 108.43966225581244, \"peak_allocated_gib\": 12.54476261138916, \"peak_reserved_gib\": 15.01953125, \"actual_steps\": 50, \"image\": \"./results/bf16-original_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_style_01_anime_woman_1024x1024_50s_42_0.png\", \"image_sha256\": \"c2d29c0ed15f0a9f94883179c9e2e863b603872a2d5b087c1165525aa1fdde48\"}"} +{"file_name": "images/1d2bd1e08f83e8b9bcfc.png", "image_id": "1d2bd1e08f83e8b9bcfc", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_natural_paczki", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 105.20605969708413, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.5981574859470129, "diffusion_seconds": 104.4433093490079, "decode_seconds": 0.5314153786748648, "png_seconds": 0.225154850166291, "upscale_inference_seconds": null, "peak_allocated_gib": 12.542878150939941, "peak_reserved_gib": 15.01953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "7a11eda19224ee3ae9925609f1a8a33362d04462d3429f092ae9265c1ea1381c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.810059119015932, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_natural_paczki\", \"started_at\": \"2026-10-21T20:35:46.549274+00:00\", \"finished_at\": \"2026-10-21T20:37:31.755331+00:00\", \"prompt_sha256\": \"2f2bd73b09b37eec803b6d3f9d88fa35dacb0c8d352f6888802bb49f4296aead\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.5981574859470129, \"seconds_inference\": 104.98090438591316, \"diffusion_seconds\": 104.4433093490079, \"decode_seconds\": 0.5314153786748648, \"png_seconds\": 0.225154850166291, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 105.20605969708413, \"peak_allocated_gib\": 12.542878150939941, \"peak_reserved_gib\": 15.01953125, \"actual_steps\": 50, \"image\": \"./results/bf16-original_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_natural_paczki_1024x1024_50s_42_0.png\", \"image_sha256\": \"7a11eda19224ee3ae9925609f1a8a33362d04462d3429f092ae9265c1ea1381c\"}"} +{"file_name": "images/50029a07c8fc7cff5f51.png", "image_id": "50029a07c8fc7cff5f51", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_menu_prices", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 105.19377028429881, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 104.44537904625759, "decode_seconds": 0.5314334710128605, "png_seconds": 0.2109874989837408, "upscale_inference_seconds": null, "peak_allocated_gib": 12.542893409729004, "peak_reserved_gib": 15.01953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "1e9b3b7a5a9aa12fdc0212f9945b54cfba94f95a5160375ab90fa597595d2bab", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.810059119015932, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T20:37:31.890432+00:00\", \"finished_at\": \"2026-10-21T20:39:17.084202+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 104.98278240393847, \"diffusion_seconds\": 104.44537904625759, \"decode_seconds\": 0.5314334710128605, \"png_seconds\": 0.2109874989837408, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 105.19377028429881, \"peak_allocated_gib\": 12.542893409729004, \"peak_reserved_gib\": 15.01953125, \"actual_steps\": 50, \"image\": \"./results/bf16-original_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_50s_42_0.png\", \"image_sha256\": \"1e9b3b7a5a9aa12fdc0212f9945b54cfba94f95a5160375ab90fa597595d2bab\"}"} +{"file_name": "images/376064482d1519a86200.png", "image_id": "376064482d1519a86200", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "bf16-original", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 105.15200828807428, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 104.44503811374307, "decode_seconds": 0.5314432671293616, "png_seconds": 0.1694333511404693, "upscale_inference_seconds": null, "peak_allocated_gib": 12.543045997619629, "peak_reserved_gib": 15.01953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "9f648ab5e69b09ade5229738aecc75cf067f317a93b2dd2e298f22530cd762a5", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": \"identical\", \"SSIM vs BF16\": 1.0, \"RGB MAE vs BF16\": 0.0}", "parameters_json": "{\"variant\": \"bf16-original\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.810059119015932, \"linear_weight_types\": {\"Parameter\": 269}, \"packed_linears\": 0, \"resident_allocated_gib\": 9.467047214508057, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T20:39:17.213369+00:00\", \"finished_at\": \"2026-10-21T20:41:02.365377+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 104.9825744559057, \"diffusion_seconds\": 104.44503811374307, \"decode_seconds\": 0.5314432671293616, \"png_seconds\": 0.1694333511404693, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 105.15200828807428, \"peak_allocated_gib\": 12.543045997619629, \"peak_reserved_gib\": 15.01953125, \"actual_steps\": 50, \"image\": \"./results/bf16-original_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_50s_42_0.png\", \"image_sha256\": \"9f648ab5e69b09ade5229738aecc75cf067f317a93b2dd2e298f22530cd762a5\"}"} +{"file_name": "images/158a39ce44669427a108.png", "image_id": "158a39ce44669427a108", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. 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Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.510908120311797, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 9.793466289993376, "decode_seconds": 0.5312836663797498, "png_seconds": 0.18022053921595216, "upscale_inference_seconds": null, "peak_allocated_gib": 9.705711841583252, "peak_reserved_gib": 13.037109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "fc98d5540821ca4b2d64682809e610017a19002b3529dac532025218cb0a9a11", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 18.286, \"SSIM vs BF16\": 0.842741, \"RGB MAE vs BF16\": 10.8025}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.221503539942205, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T20:45:37.032931+00:00\", \"finished_at\": \"2026-10-21T20:45:47.543835+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 10.330687060020864, \"diffusion_seconds\": 9.793466289993376, \"decode_seconds\": 0.5312836663797498, \"png_seconds\": 0.18022053921595216, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.510908120311797, \"peak_allocated_gib\": 9.705711841583252, \"peak_reserved_gib\": 13.037109375, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_4s_42_0.png\", \"image_sha256\": \"fc98d5540821ca4b2d64682809e610017a19002b3529dac532025218cb0a9a11\"}"} +{"file_name": "images/bf851f86aaab88a1cec1.png", "image_id": "bf851f86aaab88a1cec1", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.508442330174148, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 9.804135538171977, "decode_seconds": 0.5313487006351352, "png_seconds": 0.16690494772046804, "upscale_inference_seconds": null, "peak_allocated_gib": 9.705864429473877, "peak_reserved_gib": 13.037109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "9850620c01928b70f7812e91af26742c6bb257249bc59fb8b032a81bdfa14a0b", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 13.379, \"SSIM vs BF16\": 0.741572, \"RGB MAE vs BF16\": 24.5639}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.221503539942205, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T20:45:47.641762+00:00\", \"finished_at\": \"2026-10-21T20:45:58.150206+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 10.341536851134151, \"diffusion_seconds\": 9.804135538171977, \"decode_seconds\": 0.5313487006351352, \"png_seconds\": 0.16690494772046804, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.508442330174148, \"peak_allocated_gib\": 9.705864429473877, \"peak_reserved_gib\": 13.037109375, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_4s_42_0.png\", \"image_sha256\": \"9850620c01928b70f7812e91af26742c6bb257249bc59fb8b032a81bdfa14a0b\"}"} +{"file_name": "images/f5b6d0193a9f2ae7d16a.png", "image_id": "f5b6d0193a9f2ae7d16a", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.521786993835121, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.629698131699115, "diffusion_seconds": 9.799660610966384, "decode_seconds": 0.5312220142222941, "png_seconds": 0.1849216897971928, "upscale_inference_seconds": null, "peak_allocated_gib": 9.705803394317627, "peak_reserved_gib": 13.037109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "a6fa8d28037a3102a1990f5d533b70d198add6a8a21a730448b7f14d92e6707c", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 22.275, \"SSIM vs BF16\": 0.912708, \"RGB MAE vs BF16\": 9.1149}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.221503539942205, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_long_sentence\", \"started_at\": \"2026-10-21T20:45:58.247366+00:00\", \"finished_at\": \"2026-10-21T20:46:08.769151+00:00\", \"prompt_sha256\": \"42cdd9f49317e3a8a71484e31487bb412a61c0594d34d3e18900e94ca64b3478\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.629698131699115, \"seconds_inference\": 10.336864713113755, \"diffusion_seconds\": 9.799660610966384, \"decode_seconds\": 0.5312220142222941, \"png_seconds\": 0.1849216897971928, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.521786993835121, \"peak_allocated_gib\": 9.705803394317627, \"peak_reserved_gib\": 13.037109375, \"actual_steps\": 4, \"image\": \"./results/fp8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_long_sentence_1024x1024_4s_42_0.png\", \"image_sha256\": \"a6fa8d28037a3102a1990f5d533b70d198add6a8a21a730448b7f14d92e6707c\"}"} +{"file_name": "images/5089ffb832b92689996d.png", "image_id": "5089ffb832b92689996d", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_03_lodz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A red vintage railway destination plate on a dark blue train, natural weathering.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Łódź – Żyrardów\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Łódź – Żyrardów", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 109.63578401878476, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.7303871912881732, "diffusion_seconds": 108.7504010098055, "decode_seconds": 0.6135448440909386, "png_seconds": 0.2590457107871771, "upscale_inference_seconds": null, "peak_allocated_gib": 8.538384437561035, "peak_reserved_gib": 11.19921875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "ef1691745d5ddffa06af708fab74765fef78b26ee35f434477a30674e53f6d1e", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 25.239, \"SSIM vs BF16\": 0.91534, \"RGB MAE vs BF16\": 7.5979}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2164870789274573, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_03_lodz\", \"started_at\": \"2026-10-21T20:46:20.568068+00:00\", \"finished_at\": \"2026-10-21T20:48:10.203852+00:00\", \"prompt_sha256\": \"12fb411985827fb1f29cd500311a1c11655b06bb4264956579579547b8b27782\", \"repeat\": 0, \"first_in_process\": true, \"encode_seconds_separate\": 0.7303871912881732, \"seconds_inference\": 109.37673776689917, \"diffusion_seconds\": 108.7504010098055, \"decode_seconds\": 0.6135448440909386, \"png_seconds\": 0.2590457107871771, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 109.63578401878476, \"peak_allocated_gib\": 8.538384437561035, \"peak_reserved_gib\": 11.19921875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_03_lodz_1024x1024_50s_42_0.png\", \"image_sha256\": \"ef1691745d5ddffa06af708fab74765fef78b26ee35f434477a30674e53f6d1e\"}"} +{"file_name": "images/aa244198dd2a12da8e3d.png", "image_id": "aa244198dd2a12da8e3d", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_04_wazny", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A folded letterpress invitation on cream textured paper, realistic macro photograph.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Zażółć gęślą jaźń\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Zażółć gęślą jaźń", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.25682702893391, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; 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Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.20104865869507, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 107.44972218573093, "decode_seconds": 0.5313423010520637, "png_seconds": 0.21395141491666436, "upscale_inference_seconds": null, "peak_allocated_gib": 8.537911415100098, "peak_reserved_gib": 11.19921875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "8973ea46071bdce06772d78f79dfca73c19e9d8bdfaa1afb594fdbb36af81335", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 22.081, \"SSIM vs BF16\": 0.935534, \"RGB MAE vs BF16\": 6.834}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2164870789274573, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T21:13:29.562417+00:00\", \"finished_at\": \"2026-10-21T21:15:17.763469+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 107.98709670314565, \"diffusion_seconds\": 107.44972218573093, \"decode_seconds\": 0.5313423010520637, \"png_seconds\": 0.21395141491666436, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 108.20104865869507, \"peak_allocated_gib\": 8.537911415100098, \"peak_reserved_gib\": 11.19921875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_50s_42_0.png\", \"image_sha256\": \"8973ea46071bdce06772d78f79dfca73c19e9d8bdfaa1afb594fdbb36af81335\"}"} +{"file_name": "images/4d7dd2ffc6b3a6dc733b.png", "image_id": "4d7dd2ffc6b3a6dc733b", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.20559552591294, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 107.47316131088883, "decode_seconds": 0.5313389273360372, "png_seconds": 0.1951260301284492, "upscale_inference_seconds": null, "peak_allocated_gib": 8.538064002990723, "peak_reserved_gib": 11.19921875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "b1870700207c6e80b510d2b02102a900be698abd2efa46333a7d908a2fc1f88b", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 9.107, \"SSIM vs BF16\": 0.582276, \"RGB MAE vs BF16\": 45.9982}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2164870789274573, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T21:15:17.903148+00:00\", \"finished_at\": \"2026-10-21T21:17:06.108738+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 108.01046877494082, \"diffusion_seconds\": 107.47316131088883, \"decode_seconds\": 0.5313389273360372, \"png_seconds\": 0.1951260301284492, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 108.20559552591294, \"peak_allocated_gib\": 8.538064002990723, \"peak_reserved_gib\": 11.19921875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_50s_42_0.png\", \"image_sha256\": \"b1870700207c6e80b510d2b02102a900be698abd2efa46333a7d908a2fc1f88b\"}"} +{"file_name": "images/752154316095fe3e691d.png", "image_id": "752154316095fe3e691d", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "MOSS-Image-SFT", "variant": "fp8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "compile", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 108.21555325109512, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.629698131699115, "diffusion_seconds": 107.47624824475497, "decode_seconds": 0.531164504121989, "png_seconds": 0.20161656802520156, "upscale_inference_seconds": null, "peak_allocated_gib": 8.538002967834473, "peak_reserved_gib": 11.19921875, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "7c84bac3d632d3ffe268347cb7a0b246c586bd35f8546737cb23d6f3f424a8d7", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 26.098, \"SSIM vs BF16\": 0.976397, \"RGB MAE vs BF16\": 6.3271}", "parameters_json": "{\"variant\": \"fp8wo-core\", \"mode\": \"compile\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": true, \"compute_override\": null, \"load_seconds\": 1.2164870789274573, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.463728427886963, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_long_sentence\", \"started_at\": \"2026-10-21T21:17:06.252035+00:00\", \"finished_at\": \"2026-10-21T21:18:54.467587+00:00\", \"prompt_sha256\": \"42cdd9f49317e3a8a71484e31487bb412a61c0594d34d3e18900e94ca64b3478\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.629698131699115, \"seconds_inference\": 108.01393635291606, \"diffusion_seconds\": 107.47624824475497, \"decode_seconds\": 0.531164504121989, \"png_seconds\": 0.20161656802520156, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 108.21555325109512, \"peak_allocated_gib\": 8.538002967834473, \"peak_reserved_gib\": 11.19921875, \"actual_steps\": 50, \"image\": \"./results/fp8wo-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_long_sentence_1024x1024_50s_42_0.png\", \"image_sha256\": \"7c84bac3d632d3ffe268347cb7a0b246c586bd35f8546737cb23d6f3f424a8d7\"}"} +{"file_name": "images/861074153129b44d4051.png", "image_id": "861074153129b44d4051", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_03_lodz", "prompt": "{\"summary\":{\"meta\":[\"photo\"],\"canvas\":\"single\",\"caption\":\"A red vintage railway destination plate on a dark blue train, natural weathering.\"},\"items\":[{\"label\":\"text\",\"caption\":\"photorealistic sign with sharply defined painted glyphs\",\"text\":\"Łódź – Żyrardów\",\"bbox\":[-195,-360,195,360]}],\"bbox_coord_space\":\"abs_centralized\",\"bbox_format\":\"yxyx\"}", "expected_text": "Łódź – Żyrardów", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.355902918148786, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; 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Entirely original character and setting, no existing franchise or copyrighted character.", "expected_text": null, "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.47546285763383, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.022591732442379, "diffusion_seconds": 9.739401059690863, "decode_seconds": 0.5315226442180574, "png_seconds": 0.19864795031026006, "upscale_inference_seconds": null, "peak_allocated_gib": 9.714756488800049, "peak_reserved_gib": 12.787109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "5741ca22e6037e365388aaa1d1026d72d702dcc300ad8852ee33ee6c8885a873", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 20.661, \"SSIM vs BF16\": 0.779969, \"RGB MAE vs BF16\": 12.6421}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2219575997442007, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_01_anime_woman\", \"started_at\": \"2026-10-21T21:21:23.524425+00:00\", \"finished_at\": \"2026-10-21T21:21:33.999890+00:00\", \"prompt_sha256\": \"0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 1.022591732442379, \"seconds_inference\": 10.27681403560564, \"diffusion_seconds\": 9.739401059690863, \"decode_seconds\": 0.5315226442180574, \"png_seconds\": 0.19864795031026006, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.47546285763383, \"peak_allocated_gib\": 9.714756488800049, \"peak_reserved_gib\": 12.787109375, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_style_01_anime_woman_1024x1024_4s_42_0.png\", \"image_sha256\": \"5741ca22e6037e365388aaa1d1026d72d702dcc300ad8852ee33ee6c8885a873\"}"} +{"file_name": "images/da519dcd3507eb4af752.png", "image_id": "da519dcd3507eb4af752", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_natural_paczki", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.105001490097493, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.5981574859470129, "diffusion_seconds": 9.37105844495818, "decode_seconds": 0.5314156673848629, "png_seconds": 0.196525436360389, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712437152862549, "peak_reserved_gib": 12.787109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "ff2ad52b0b666f03160c476d28eba1bf57dfb6f7153a126769758f02fd0e6dad", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 22.124, \"SSIM vs BF16\": 0.753348, \"RGB MAE vs BF16\": 11.8094}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2219575997442007, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_natural_paczki\", \"started_at\": \"2026-10-21T21:21:34.101522+00:00\", \"finished_at\": \"2026-10-21T21:21:44.206522+00:00\", \"prompt_sha256\": \"2f2bd73b09b37eec803b6d3f9d88fa35dacb0c8d352f6888802bb49f4296aead\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.5981574859470129, \"seconds_inference\": 9.908475582953542, \"diffusion_seconds\": 9.37105844495818, \"decode_seconds\": 0.5314156673848629, \"png_seconds\": 0.196525436360389, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.105001490097493, \"peak_allocated_gib\": 9.712437152862549, \"peak_reserved_gib\": 12.787109375, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_natural_paczki_1024x1024_4s_42_0.png\", \"image_sha256\": \"ff2ad52b0b666f03160c476d28eba1bf57dfb6f7153a126769758f02fd0e6dad\"}"} +{"file_name": "images/e5c67d4bb9ed01f71501.png", "image_id": "e5c67d4bb9ed01f71501", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_menu_prices", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.095955242868513, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 9.377921550069004, "decode_seconds": 0.5315249469131231, "png_seconds": 0.18064993200823665, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712452411651611, "peak_reserved_gib": 12.787109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "f4cade105a46691871de1df04ae002795dffa3a2278b687be53913d386bb72e9", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 19.286, \"SSIM vs BF16\": 0.874188, \"RGB MAE vs BF16\": 10.2343}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2219575997442007, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T21:21:44.303653+00:00\", \"finished_at\": \"2026-10-21T21:21:54.399606+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 9.91530467895791, \"diffusion_seconds\": 9.377921550069004, \"decode_seconds\": 0.5315249469131231, \"png_seconds\": 0.18064993200823665, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.095955242868513, \"peak_allocated_gib\": 9.712452411651611, \"peak_reserved_gib\": 12.787109375, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_4s_42_0.png\", \"image_sha256\": \"f4cade105a46691871de1df04ae002795dffa3a2278b687be53913d386bb72e9\"}"} +{"file_name": "images/75d95b4ac9618d7a3dff.png", "image_id": "75d95b4ac9618d7a3dff", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 4, "cfg": 1.0, "mode": "eager", "student": true, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 10.09660129295662, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 9.387536413036287, "decode_seconds": 0.5312839890830219, "png_seconds": 0.1716165728867054, "upscale_inference_seconds": null, "peak_allocated_gib": 9.712604999542236, "peak_reserved_gib": 12.787109375, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "6c15c0c4dffd9bf6dd02b34509522e8043eb9cd76050cd74008c5fab094d5a71", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 15.507, \"SSIM vs BF16\": 0.785983, \"RGB MAE vs BF16\": 16.8445}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 4, \"cfg\": 1.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": {\"sha256\": \"154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f\", \"dtype\": \"float32\", \"merged\": false, \"helper_sha256\": \"6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3\"}, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2219575997442007, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T21:21:54.499888+00:00\", \"finished_at\": \"2026-10-21T21:22:04.596488+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 9.92498425906524, \"diffusion_seconds\": 9.387536413036287, \"decode_seconds\": 0.5312839890830219, \"png_seconds\": 0.1716165728867054, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 10.09660129295662, \"peak_allocated_gib\": 9.712604999542236, \"peak_reserved_gib\": 12.787109375, \"actual_steps\": 4, \"image\": \"./results/int8wo-core_eager-student-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_4s_42_0.png\", \"image_sha256\": \"6c15c0c4dffd9bf6dd02b34509522e8043eb9cd76050cd74008c5fab094d5a71\"}"} +{"file_name": "images/070022f2735425e300e2.png", "image_id": "070022f2735425e300e2", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. 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Entirely original character and setting, no existing franchise or copyrighted character.", "expected_text": null, "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 161.1597461490892, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 1.022591732442379, "diffusion_seconds": 160.42182869417593, "decode_seconds": 0.5313481278717518, "png_seconds": 0.20055207516998053, "upscale_inference_seconds": null, "peak_allocated_gib": 8.547200202941895, "peak_reserved_gib": 11.501953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "0eecfc09f38c3d5ee1054f973c2f1334b944f661665ec455460ab0553b352f30", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 26.794, \"SSIM vs BF16\": 0.933547, \"RGB MAE vs BF16\": 5.7836}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2180510531179607, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"style_01_anime_woman\", \"started_at\": \"2026-10-21T21:56:36.133312+00:00\", \"finished_at\": \"2026-10-21T21:59:17.293051+00:00\", \"prompt_sha256\": \"0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 1.022591732442379, \"seconds_inference\": 160.95919355284423, \"diffusion_seconds\": 160.42182869417593, \"decode_seconds\": 0.5313481278717518, \"png_seconds\": 0.20055207516998053, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 161.1597461490892, \"peak_allocated_gib\": 8.547200202941895, \"peak_reserved_gib\": 11.501953125, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-conda3cd376f_style_01_anime_woman_1024x1024_50s_42_0.png\", \"image_sha256\": \"0eecfc09f38c3d5ee1054f973c2f1334b944f661665ec455460ab0553b352f30\"}"} +{"file_name": "images/a7760c41c6987c010402.png", "image_id": "a7760c41c6987c010402", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_natural_paczki", "prompt": "A photorealistic Polish bakery storefront in soft morning light. Its large main sign must read exactly: ŚWIEŻE PĄCZKI. Preserve every Polish diacritic. Dark wood, gold serif letters, pastries behind glass, realistic reflections. No other text, logos or watermarks.", "expected_text": "ŚWIEŻE PĄCZKI", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.38332374487072, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.5981574859470129, "diffusion_seconds": 156.62237178487703, "decode_seconds": 0.5313038732856512, "png_seconds": 0.22370795020833611, "upscale_inference_seconds": null, "peak_allocated_gib": 8.544636726379395, "peak_reserved_gib": 11.501953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "85607e255f0c3b8ec50c9ead4f3737dce1861f64e987cf186c9b0d1dbc2bf80a", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 23.259, \"SSIM vs BF16\": 0.860534, \"RGB MAE vs BF16\": 9.0797}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2180510531179607, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_natural_paczki\", \"started_at\": \"2026-10-21T21:59:17.392009+00:00\", \"finished_at\": \"2026-10-21T22:01:54.775327+00:00\", \"prompt_sha256\": \"2f2bd73b09b37eec803b6d3f9d88fa35dacb0c8d352f6888802bb49f4296aead\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.5981574859470129, \"seconds_inference\": 157.15961534390226, \"diffusion_seconds\": 156.62237178487703, \"decode_seconds\": 0.5313038732856512, \"png_seconds\": 0.22370795020833611, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 157.38332374487072, \"peak_allocated_gib\": 8.544636726379395, \"peak_reserved_gib\": 11.501953125, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-conda3cd376f_pl_natural_paczki_1024x1024_50s_42_0.png\", \"image_sha256\": \"85607e255f0c3b8ec50c9ead4f3737dce1861f64e987cf186c9b0d1dbc2bf80a\"}"} +{"file_name": "images/bfdede5da9f212f19990.png", "image_id": "bfdede5da9f212f19990", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_menu_prices", "prompt": "A clean straight-on photograph of an elegant Polish cafe menu board. Exactly three lines, spelled precisely:\nMENU\nKawa 12,50 zł\nPączek 7,00 zł\nReadable chalk lettering, correct Polish letters and decimal commas. Simple light wall, no other text.", "expected_text": "MENU\nKawa 12,50 zł\nPączek 7,00 zł", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.36979677993804, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.611250888556242, "diffusion_seconds": 156.62113357381895, "decode_seconds": 0.5312711950391531, "png_seconds": 0.2114529157988727, "upscale_inference_seconds": null, "peak_allocated_gib": 8.544651985168457, "peak_reserved_gib": 11.501953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "3bfcbedbb32b63a6b0eda10765612d514d45377d4167f8175c21043d75dd59c9", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 27.386, \"SSIM vs BF16\": 0.979957, \"RGB MAE vs BF16\": 4.7492}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2180510531179607, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_menu_prices\", \"started_at\": \"2026-10-21T22:01:54.877551+00:00\", \"finished_at\": \"2026-10-21T22:04:32.247347+00:00\", \"prompt_sha256\": \"836c3bcd25cc8f5a28a98fda5d082ce587039dcb9263f36da58c97c415e1601b\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.611250888556242, \"seconds_inference\": 157.15834344318137, \"diffusion_seconds\": 156.62113357381895, \"decode_seconds\": 0.5312711950391531, \"png_seconds\": 0.2114529157988727, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 157.36979677993804, \"peak_allocated_gib\": 8.544651985168457, \"peak_reserved_gib\": 11.501953125, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-conda3cd376f_pl_menu_prices_1024x1024_50s_42_0.png\", \"image_sha256\": \"3bfcbedbb32b63a6b0eda10765612d514d45377d4167f8175c21043d75dd59c9\"}"} +{"file_name": "images/292b6066678e9cf3a0aa.png", "image_id": "292b6066678e9cf3a0aa", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_poster_multiline", "prompt": "A professionally designed Polish autumn cultural event poster, clear sophisticated typography, warm orange and navy graphic leaves. Render exactly three legible lines:\nJESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY\nCorrect Polish diacritics, balanced spacing, no additional words or watermarks.", "expected_text": "JESIEŃ W ŁODZI\n21 PAŹDZIERNIKA\nWSTĘP WOLNY", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.40904848417267, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.6463502147234976, "diffusion_seconds": 156.6827518781647, "decode_seconds": 0.5314118391834199, "png_seconds": 0.1888545099645853, "upscale_inference_seconds": null, "peak_allocated_gib": 8.544804573059082, "peak_reserved_gib": 11.501953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "73c9d95468c70e476d8f4d62f55bb27fcb0b3332bfede5667b6d0263046d4837", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 11.949, \"SSIM vs BF16\": 0.716904, \"RGB MAE vs BF16\": 27.2139}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 1024, \"height\": 1024, \"noise_dtype\": \"float32\", \"student\": null, \"compile_dynamic\": false, \"compute_override\": null, \"load_seconds\": 1.2180510531179607, \"linear_weight_types\": {\"Parameter\": 41, \"AffineQuantizedTensor\": 228}, \"packed_linears\": 228, \"resident_allocated_gib\": 5.470468997955322, \"vae_dtype\": \"torch.float32\", \"vae_tiling\": false, \"status\": \"ok\", \"case\": \"pl_poster_multiline\", \"started_at\": \"2026-10-21T22:04:32.344299+00:00\", \"finished_at\": \"2026-10-21T22:07:09.753347+00:00\", \"prompt_sha256\": \"e9f32b5a3bc796de96f1b199182702faac7dfdeab1798d85799e820b1092c6f8\", \"repeat\": 0, \"first_in_process\": false, \"encode_seconds_separate\": 0.6463502147234976, \"seconds_inference\": 157.2201933832839, \"diffusion_seconds\": 156.6827518781647, \"decode_seconds\": 0.5314118391834199, \"png_seconds\": 0.1888545099645853, \"negative_encode_seconds_cold\": 0.6952687790617347, \"seconds_including_png\": 157.40904848417267, \"peak_allocated_gib\": 8.544804573059082, \"peak_reserved_gib\": 11.501953125, \"actual_steps\": 50, \"image\": \"./results/int8wo-core_eager-sft-float32-torch2.10.0-conda3cd376f_pl_poster_multiline_1024x1024_50s_42_0.png\", \"image_sha256\": \"73c9d95468c70e476d8f4d62f55bb27fcb0b3332bfede5667b6d0263046d4837\"}"} +{"file_name": "images/2a546b10d50ecbaa404c.png", "image_id": "2a546b10d50ecbaa404c", "run_id": "moss-image-20261021", "record_type": "quality", "case_id": "pl_long_sentence", "prompt": "An editorial photograph of a cream postcard on a wooden desk with a pen and soft side light. The postcard has one clearly readable handwritten Polish sentence, exactly: Zażółć gęślą jaźń – piękny dzień w Łodzi! Preserve all letters, diacritics, punctuation and spaces. No other text.", "expected_text": "Zażółć gęślą jaźń – piękny dzień w Łodzi!", "model": "MOSS-Image-SFT", "variant": "int8wo-core", "seed": 42, "steps": 50, "cfg": 3.0, "mode": "eager", "student": false, "compute_override": null, "width": 1024, "height": 1024, "scale": null, "upscale_precision": null, "seconds": 157.40762482816353, "source_seconds": null, "source_plus_upscale_seconds": null, "timing_scope": "cached conditioning; diffusion + VAE + PNG", "prompt_encode_seconds": 0.629698131699115, "diffusion_seconds": 156.66033721901476, "decode_seconds": 0.5312601709738374, "png_seconds": 0.20993199897930026, "upscale_inference_seconds": null, "peak_allocated_gib": 8.544743537902832, "peak_reserved_gib": 11.501953125, "gpu": "NVIDIA GeForce RTX 5060 Ti", "torch": "2.10.0", "vae_dtype": "torch.float32", "encoder": "original_bf16", "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "image_sha256": "5b342d2f233ed6fbd97d30cf6762a31d1c8c80eb9ed88ff002e213c6a71b5084", "source_image_id": null, "measurement_count": 1, "human_rating": null, "human_note": null, "metrics_json": "{\"PSNR dB vs BF16\": 29.261, \"SSIM vs BF16\": 0.983927, \"RGB MAE vs BF16\": 4.4687}", "parameters_json": "{\"variant\": \"int8wo-core\", \"mode\": \"eager\", \"source_revision\": \"fc5de0d56fc910cbca6f6625a70f5f582b26deb1\", \"gpu\": \"NVIDIA GeForce RTX 5060 Ti\", \"sm\": [12, 0], \"versions\": {\"torch\": \"2.10.0\", \"torchao\": \"0.15.0\", \"diffusers\": \"0.38.0\", \"transformers\": \"5.12.1\", \"accelerate\": \"1.12.0\"}, \"encoder\": \"original_bf16\", \"timing_scope\": \"cached conditioning; diffusion + VAE + PNG\", \"encoder_device\": \"cpu\", \"encoder_torch\": \"2.10.0+cu128\", \"encoder_transformers\": \"5.12.1\", \"encoder_inference_mode\": false, \"conditioning_sha256\": \"a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65\", \"steps\": 50, \"cfg\": 3.0, \"seed\": 42, \"width\": 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"image_sha256": "5e20462cff898b2a2671d2b77ec10cbbcdfe58d579b17f56bea351e0c177c199"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": "runs/moss-image-20261021/diagnostics/images/1c98e0064c87a5a1073a.png", "record": {"variant": "int8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": null, "load_seconds": 1.1603147750720382, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "pl_01_wrozka", "started_at": "2026-10-21T18:18:15.626160+00:00", "finished_at": "2026-10-21T18:25:04.343102+00:00", "prompt_sha256": "2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 0.7458397052250803, "seconds_inference": 408.5490242661908, "diffusion_seconds": 407.9189877281897, "decode_seconds": 0.6129406807012856, "png_seconds": 0.1679174299351871, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 408.7169423168525, "peak_allocated_gib": 8.545186042785645, "peak_reserved_gib": 11.236328125, "actual_steps": 2, "image": "./diagnostics/int8wo-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_01_wrozka_1024x1024_2s_42_0.png", "image_sha256": "d9dbea079e4ecce0b0ba6dd0741d28308efd25908f9718cc4075c2e7cb8ec5cd"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": "runs/moss-image-20261021/diagnostics/images/52f3c682591b94cb268a.png", "record": {"variant": "fp8w8a8-tensor-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 3.4931459608487785, "linear_weight_types": {"Parameter": 41, "LinearActivationQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.459343433380127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "pl_01_wrozka", "started_at": "2026-10-21T18:25:19.529328+00:00", "finished_at": "2026-10-21T18:25:26.090336+00:00", "prompt_sha256": "2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 0.7458397052250803, "seconds_inference": 6.392205279320478, "diffusion_seconds": 5.773751961067319, "decode_seconds": 0.610654610209167, "png_seconds": 0.168806707020849, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 6.561012597288936, "peak_allocated_gib": 8.53406047821045, "peak_reserved_gib": 11.548828125, "actual_steps": 2, "image": "./diagnostics/fp8w8a8-tensor-core_eager-sft-float32-torch2.10.0-conda3cd376f_pl_01_wrozka_1024x1024_2s_42_0.png", "image_sha256": "21792df909858b5df1795ceffb40a94378da4e660b032ab41de68d2d4442cd11"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": "runs/moss-image-20261021/diagnostics/images/cbdb4b45e99e6f9f1c95.png", "record": {"variant": "fp8w8a8-tensor-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": null, "load_seconds": 1.174389448016882, "linear_weight_types": {"Parameter": 41, "LinearActivationQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.459343433380127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "pl_01_wrozka", "started_at": "2026-10-21T18:25:35.612442+00:00", "finished_at": "2026-10-21T18:25:43.926213+00:00", "prompt_sha256": "2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 0.7458397052250803, "seconds_inference": 8.15055663511157, "diffusion_seconds": 7.497644117102027, "decode_seconds": 0.6119717080146074, "png_seconds": 0.1632167878560722, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 8.313774223905057, "peak_allocated_gib": 8.53406047821045, "peak_reserved_gib": 11.16015625, "actual_steps": 2, "image": "./diagnostics/fp8w8a8-tensor-core_compile-dynamic-sft-float32-torch2.10.0-conda3cd376f_pl_01_wrozka_1024x1024_2s_42_0.png", "image_sha256": "0876b5da870c3454e2e3a3d53170af5086b350728a209cfe2f5fcf26a7f55be7"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 2.6278616189956665, "linear_weight_types": {"Parameter": 41, "NVFP4Tensor": 228}, "packed_linears": 228, "resident_allocated_gib": 3.731316089630127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "RuntimeError", "error": "shape '[1, 262]' is invalid for input of size 807168", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n ^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 121, in __torch_dispatch__\n return NVFP4_OPS_TABLE[func](func, types, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 662, in nvfp4_linear\n input_tensor = NVFP4Tensor.to_nvfp4(\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 162, in to_nvfp4\n blockwise_scales.view(scale_shape)\nRuntimeError: shape '[1, 262]' is invalid for input of size 807168\n", "peak_allocated_gib": 4.451931953430176, "peak_reserved_gib": 4.693359375}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": "runs/moss-image-20261021/diagnostics/images/e14ba57703a685f30ce0.png", "record": {"variant": "nvfp4-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": "nvfp4-weight-only", "load_seconds": 0.9601662680506706, "linear_weight_types": {"Parameter": 41, "NVFP4Tensor": 228}, "packed_linears": 228, "resident_allocated_gib": 3.731316089630127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "pl_01_wrozka", "started_at": "2026-10-21T18:26:39.938993+00:00", "finished_at": "2026-10-21T18:26:52.144890+00:00", "prompt_sha256": "2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 0.7458397052250803, "seconds_inference": 11.980466770939529, "diffusion_seconds": 11.34522178210318, "decode_seconds": 0.6167102716863155, "png_seconds": 0.22543772403150797, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 12.205905436072499, "peak_allocated_gib": 6.808611869812012, "peak_reserved_gib": 10.33203125, "actual_steps": 2, "image": "./diagnostics/nvfp4-core_eager-sft-float32-wo-runtime-torch2.7.0-conda3cd376f_pl_01_wrozka_1024x1024_2s_42_0.png", "image_sha256": "a01bd10df9b85518d2829a836a609c650adffad749a9d814cc102f1e45e8d1bd"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": "nvfp4-weight-only", "load_seconds": 0.9696106393821537, "linear_weight_types": {"Parameter": 41, "NVFP4Tensor": 228}, "packed_linears": 228, "resident_allocated_gib": 3.731316089630127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "Unsupported", "error": "Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1749, in _wrapped_call_impl\n return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 659, in _fn\n raise e.with_traceback(None) from None\ntorch._dynamo.exc.Unsupported: Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n\n", "peak_allocated_gib": 4.304730415344238, "peak_reserved_gib": 4.455078125}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 2.0209629642777145, "linear_weight_types": {"NVFP4Tensor": 269}, "packed_linears": 269, "resident_allocated_gib": 2.6940126419067383, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "AssertionError", "error": "", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 239, in forward\n time = self.time_embedding(embedding.to(self.time_embedding[0].weight.dtype)).float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/container.py\", line 240, in forward\n input = module(input)\n ^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 121, in __torch_dispatch__\n return NVFP4_OPS_TABLE[func](func, types, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 668, in nvfp4_linear\n return _addmm_nvfp4_dispatch(input_tensor, weight_tensor.t(), func, bias=bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 615, in _addmm_nvfp4_dispatch\n assert b._per_tensor_scale is None and a._per_tensor_scale is None\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError\n", "peak_allocated_gib": 2.9350104331970215, "peak_reserved_gib": 2.9765625}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": "runs/moss-image-20261021/diagnostics/images/b80773102daf7452481c.png", "record": {"variant": "nvfp4-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": "nvfp4-weight-only", "load_seconds": 0.8013428850099444, "linear_weight_types": {"NVFP4Tensor": 269}, "packed_linears": 269, "resident_allocated_gib": 2.6940126419067383, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "pl_01_wrozka", "started_at": "2026-10-21T18:27:19.376057+00:00", "finished_at": "2026-10-21T18:27:32.580786+00:00", "prompt_sha256": "2d2d07a73032743586979845f95f07851a44b5809aab4b28afd9b936d8b7dcff", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 0.7458397052250803, "seconds_inference": 12.948648813180625, "diffusion_seconds": 12.310797940008342, "decode_seconds": 0.6180242127738893, "png_seconds": 0.2560838349163532, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 13.204733319114894, "peak_allocated_gib": 5.7686991691589355, "peak_reserved_gib": 9.494140625, "actual_steps": 2, "image": "./diagnostics/nvfp4-max_eager-sft-float32-wo-runtime-torch2.7.0-conda3cd376f_pl_01_wrozka_1024x1024_2s_42_0.png", "image_sha256": "761ecfc0a241a2e4d4642602d53d8f78f4a79b6b90123f8874c93cd0c519358f"}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-max", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": "nvfp4-weight-only", "load_seconds": 0.7954691299237311, "linear_weight_types": {"NVFP4Tensor": 269}, "packed_linears": 269, "resident_allocated_gib": 2.6940126419067383, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "Unsupported", "error": "Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1749, in _wrapped_call_impl\n return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 659, in _fn\n raise e.with_traceback(None) from None\ntorch._dynamo.exc.Unsupported: Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n\n", "peak_allocated_gib": 4.52494478225708, "peak_reserved_gib": 4.98046875}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 2.766847232822329, "linear_weight_types": {"Parameter": 41, "NVFP4Tensor": 228}, "packed_linears": 228, "resident_allocated_gib": 3.731316089630127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "RuntimeError", "error": "shape '[1, 262]' is invalid for input of size 807168", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n ^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 121, in __torch_dispatch__\n return NVFP4_OPS_TABLE[func](func, types, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 662, in nvfp4_linear\n input_tensor = NVFP4Tensor.to_nvfp4(\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 162, in to_nvfp4\n blockwise_scales.view(scale_shape)\nRuntimeError: shape '[1, 262]' is invalid for input of size 807168\n", "peak_allocated_gib": 4.451931953430176, "peak_reserved_gib": 4.693359375}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": "nvfp4-weight-only", "load_seconds": 1.0431118747219443, "linear_weight_types": {"Parameter": 41, "NVFP4Tensor": 228}, "packed_linears": 228, "resident_allocated_gib": 3.731316089630127, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "Unsupported", "error": "Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1749, in _wrapped_call_impl\n return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 659, in _fn\n raise e.with_traceback(None) from None\ntorch._dynamo.exc.Unsupported: Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n\n", "peak_allocated_gib": 4.273480415344238, "peak_reserved_gib": 4.4296875}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 2.0839812248013914, "linear_weight_types": {"NVFP4Tensor": 269}, "packed_linears": 269, "resident_allocated_gib": 2.6940126419067383, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "AssertionError", "error": "", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 239, in forward\n time = self.time_embedding(embedding.to(self.time_embedding[0].weight.dtype)).float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/container.py\", line 240, in forward\n input = module(input)\n ^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 121, in __torch_dispatch__\n return NVFP4_OPS_TABLE[func](func, types, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 668, in nvfp4_linear\n return _addmm_nvfp4_dispatch(input_tensor, weight_tensor.t(), func, bias=bias)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./deps/torchao/prototype/mx_formats/nvfp4_tensor.py\", line 615, in _addmm_nvfp4_dispatch\n assert b._per_tensor_scale is None and a._per_tensor_scale is None\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError\n", "peak_allocated_gib": 2.9350104331970215, "peak_reserved_gib": 2.9765625}} +{"source_file": "diagnostics/measurements.jsonl", "image_file": null, "record": {"variant": "nvfp4-max", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 2, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": true, "compute_override": "nvfp4-weight-only", "load_seconds": 0.8179799988865852, "linear_weight_types": {"NVFP4Tensor": 269}, "packed_linears": 269, "resident_allocated_gib": 2.6940126419067383, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "Unsupported", "error": "Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 227, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1749, in _wrapped_call_impl\n return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 659, in _fn\n raise e.with_traceback(None) from None\ntorch._dynamo.exc.Unsupported: Data dependent operator\n Explanation: Operator `aten._local_scalar_dense.default` has a non-Tensor output whose value is dependent on the data of Tensor inputs.\n Hint: Enable tracing of data-dependent output operators with `torch._dynamo.config.capture_scalar_outputs = True`\n\n Developer debug context: aten._local_scalar_dense.default\n\n\nfrom user code:\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 143, in forward\n q = self.q_norm(self.proj['q'](y).unflatten(-1, (self.heads, -1))).flatten(2)\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/linear.py\", line 125, in forward\n return F.linear(input, self.weight, self.bias)\n\nSet TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS=\"+dynamo\"\n\n", "peak_allocated_gib": 4.52494478225708, "peak_reserved_gib": 4.98046875}} +{"source_file": "noise-control/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/15ea736744692742c046.png", "record": {"variant": "bf16-original", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "bfloat16", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 1.914226220920682, "linear_weight_types": {"Parameter": 269}, "packed_linears": 0, "resident_allocated_gib": 9.467047214508057, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:55:06.026946+00:00", "finished_at": "2026-10-21T17:57:37.727509+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 1.1287592169828713, "seconds_inference": 151.49721682583913, "diffusion_seconds": 150.8596268859692, "decode_seconds": 0.624524689745158, "png_seconds": 0.20334647316485643, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 151.70056385966018, "peak_allocated_gib": 12.544709205627441, "peak_reserved_gib": 14.595703125, "actual_steps": 50, "image": "./noise-control/bf16-original_eager-sft-float32-noisebfloat16-torch2.10.0-conda3cd376f_style_02_river_bakery_1024x1024_50s_42_0.png", "image_sha256": "3f811a06248f65e2ad57ab5c30bb52fd4146e1cc3a5e946ab798700602ee2b23"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/b8d8ada53494cfe20f4a.png", "record": {"variant": "fp8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.361059573944658, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 11.718226354103535, "seconds_including_png": 12.01337208878249, "peak_allocated_gib": 9.706360340118408, "peak_reserved_gib": 13.052734375, "actual_steps": 4, "image": "./results/fp8wo-core_eager_style_01_anime_woman_1024x1024_4s_42_0.png", "image_sha256": "20d1d38c2200ae29d63c7514739a3afbf6b3a0540bf3d9e2ca54f3b716b9503d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/b08acb6a5c86e87ead4c.png", "record": {"variant": "fp8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.361059573944658, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 11.4366230010055, "seconds_including_png": 11.726596078369766, "peak_allocated_gib": 9.706360340118408, "peak_reserved_gib": 13.052734375, "actual_steps": 4, "image": "./results/fp8wo-core_eager_style_01_anime_woman_1024x1024_4s_42_1.png", "image_sha256": "20d1d38c2200ae29d63c7514739a3afbf6b3a0540bf3d9e2ca54f3b716b9503d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/5a4a0754bb6e0a297557.png", "record": {"variant": "fp8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.361059573944658, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 11.478957352228463, "seconds_including_png": 11.768902686890215, "peak_allocated_gib": 9.70710802078247, "peak_reserved_gib": 13.052734375, "actual_steps": 4, "image": "./results/fp8wo-core_eager_style_02_river_bakery_1024x1024_4s_42_0.png", "image_sha256": "a2ccb19b267a040b471544f35642e997ff5b05cf4e45f241b5fb61cf52eebee1"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/4a8509da4251815eba88.png", "record": {"variant": "fp8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.361059573944658, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 11.4864284042269, "seconds_including_png": 11.773383881896734, "peak_allocated_gib": 9.70710802078247, "peak_reserved_gib": 13.052734375, "actual_steps": 4, "image": "./results/fp8wo-core_eager_style_02_river_bakery_1024x1024_4s_42_1.png", "image_sha256": "a2ccb19b267a040b471544f35642e997ff5b05cf4e45f241b5fb61cf52eebee1"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/088992279d694c6f65ec.png", "record": {"variant": "fp8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "load_seconds": 1.3555215378291905, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:08:43.178181+00:00", "finished_at": "2026-10-21T17:11:05.508582+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 142.04836957529187, "seconds_including_png": 142.3304060162045, "peak_allocated_gib": 8.539727210998535, "peak_reserved_gib": 11.4921875, "actual_steps": 50, "image": "./results/fp8wo-core_compile_style_01_anime_woman_1024x1024_50s_42_0.png", "image_sha256": "2584a20f68b6a3067756597e50f399abf7354fe528512457b4f09e2d2a57f67e"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/e1b30b210894f54d2caf.png", "record": {"variant": "fp8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "load_seconds": 1.3555215378291905, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:11:05.666561+00:00", "finished_at": "2026-10-21T17:13:24.657832+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 138.72365382034332, "seconds_including_png": 138.99126999732107, "peak_allocated_gib": 8.539483070373535, "peak_reserved_gib": 11.4921875, "actual_steps": 50, "image": "./results/fp8wo-core_compile_style_02_river_bakery_1024x1024_50s_42_0.png", "image_sha256": "d78c0e9eaf752404d2bbc80bbdcd06e8696085e56a96509491cedb7e725c305d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/de52fbfdf929940f0781.png", "record": {"variant": "int8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 3.8023760630749166, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:13:38.179648+00:00", "finished_at": "2026-10-21T17:13:49.409901+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 10.929705169983208, "seconds_including_png": 11.230257309041917, "peak_allocated_gib": 9.713100910186768, "peak_reserved_gib": 12.798828125, "actual_steps": 4, "image": "./results/int8wo-core_eager_style_01_anime_woman_1024x1024_4s_42_0.png", "image_sha256": "281d4719f236ddddb28e6e46b016b74a8dea7b2994d1ceebb6dca4f627d93dbd"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/3ada57b788a065277443.png", "record": {"variant": "int8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 3.8023760630749166, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:13:49.537140+00:00", "finished_at": "2026-10-21T17:14:00.537492+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 10.710600984748453, "seconds_including_png": 11.000355581752956, "peak_allocated_gib": 9.713100910186768, "peak_reserved_gib": 12.798828125, "actual_steps": 4, "image": "./results/int8wo-core_eager_style_01_anime_woman_1024x1024_4s_42_1.png", "image_sha256": "281d4719f236ddddb28e6e46b016b74a8dea7b2994d1ceebb6dca4f627d93dbd"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/827847d09cc959e73d57.png", "record": {"variant": "int8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 3.8023760630749166, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:14:00.660492+00:00", "finished_at": "2026-10-21T17:14:11.677454+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 10.736462960019708, "seconds_including_png": 11.01696232194081, "peak_allocated_gib": 9.71384859085083, "peak_reserved_gib": 12.798828125, "actual_steps": 4, "image": "./results/int8wo-core_eager_style_02_river_bakery_1024x1024_4s_42_0.png", "image_sha256": "bf72a6193ff3dd2296e912e7c52c0665451d7dda4a36302a3d025f41db9f020d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/e1f0f34b3bd5d5381804.png", "record": {"variant": "int8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 3.8023760630749166, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:14:11.801255+00:00", "finished_at": "2026-10-21T17:14:22.817882+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 10.736123880837113, "seconds_including_png": 11.016629223711789, "peak_allocated_gib": 9.71384859085083, "peak_reserved_gib": 12.798828125, "actual_steps": 4, "image": "./results/int8wo-core_eager_style_02_river_bakery_1024x1024_4s_42_1.png", "image_sha256": "bf72a6193ff3dd2296e912e7c52c0665451d7dda4a36302a3d025f41db9f020d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/91824ac9703328f355ab.png", "record": {"variant": "fp8wo-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.2480180179700255, "linear_weight_types": {"AffineQuantizedTensor": 269}, "packed_linears": 269, "resident_allocated_gib": 4.74094295501709, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:14:31.474214+00:00", "finished_at": "2026-10-21T17:14:43.650014+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 11.883437611628324, "seconds_including_png": 12.175799138844013, "peak_allocated_gib": 8.988633155822754, "peak_reserved_gib": 12.537109375, "actual_steps": 4, "image": "./results/fp8wo-max_eager_style_01_anime_woman_1024x1024_4s_42_0.png", "image_sha256": "00f084ee870875c685a1b4deba364a189c33bdb5d852fa2c9113b60f6fb57bba"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/60e50d2b6e9654fe4baf.png", "record": {"variant": "fp8wo-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.2480180179700255, "linear_weight_types": {"AffineQuantizedTensor": 269}, "packed_linears": 269, "resident_allocated_gib": 4.74094295501709, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:14:43.772328+00:00", "finished_at": "2026-10-21T17:14:55.734350+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 11.669820551760495, "seconds_including_png": 11.962027656845748, "peak_allocated_gib": 8.988633155822754, "peak_reserved_gib": 12.537109375, "actual_steps": 4, "image": "./results/fp8wo-max_eager_style_01_anime_woman_1024x1024_4s_42_1.png", "image_sha256": "00f084ee870875c685a1b4deba364a189c33bdb5d852fa2c9113b60f6fb57bba"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/7838e9f3c0cdcd0d3428.png", "record": {"variant": "fp8wo-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.2480180179700255, "linear_weight_types": {"AffineQuantizedTensor": 269}, "packed_linears": 269, "resident_allocated_gib": 4.74094295501709, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:14:55.876721+00:00", "finished_at": "2026-10-21T17:15:07.849955+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 11.69585635093972, "seconds_including_png": 11.973231663927436, "peak_allocated_gib": 8.989991188049316, "peak_reserved_gib": 12.537109375, "actual_steps": 4, "image": "./results/fp8wo-max_eager_style_02_river_bakery_1024x1024_4s_42_0.png", "image_sha256": "cf1c3ea6f93b9356af000d5cfb7b2b579712740f6c4c9455500c3135929ac10b"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/f4a255890a2bb273681f.png", "record": {"variant": "fp8wo-max", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.2480180179700255, "linear_weight_types": {"AffineQuantizedTensor": 269}, "packed_linears": 269, "resident_allocated_gib": 4.74094295501709, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:15:07.969032+00:00", "finished_at": "2026-10-21T17:15:19.942461+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 1, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 11.695967226754874, "seconds_including_png": 11.973430464975536, "peak_allocated_gib": 8.989991188049316, "peak_reserved_gib": 12.537109375, "actual_steps": 4, "image": "./results/fp8wo-max_eager_style_02_river_bakery_1024x1024_4s_42_1.png", "image_sha256": "cf1c3ea6f93b9356af000d5cfb7b2b579712740f6c4c9455500c3135929ac10b"}} +{"source_file": "results/measurements.jsonl", "image_file": null, "record": {"variant": "fp8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 4, "cfg": 1.0, "seed": 42, "width": 1024, "height": 1024, "student": {"sha256": "154c7f1455c3bf9925945c2f1ea2e4f09d0d0c67256081384a094b2b585f913f", "dtype": "float32", "merged": false, "helper_sha256": "6e2a6067751b091efb5b1cd010f5e4885faa838542ff3c0a644ad519162605f3"}, "load_seconds": 1.361091681290418, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "error", "error_type": "InternalTorchDynamoError", "error": "ModuleNotFoundError: No module named 'moss_benchmark_student'", "traceback": "Traceback (most recent call last):\n File \"[redacted-runtime-root]/scripts/benchmark-moss-image.py\", line 166, in infer\n result = pipe(**cond, width=args.width, height=args.height,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 116, in decorate_context\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 413, in __call__\n prediction = self.transformer(latents, timestep, positive, positive_mask).sample.float()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1751, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"./hf-cache/models--OpenMOSS-Team--MOSS-Image-SFT/snapshots/fc5de0d56fc910cbca6f6625a70f5f582b26deb1/pipeline_moss_image.py\", line 255, in forward\n x = layer(x, rope, mod[index:index + 1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1749, in _wrapped_call_impl\n return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py\", line 655, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1762, in _call_impl\n return forward_call(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 1432, in __call__\n return self._torchdynamo_orig_callable(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 598, in __call__\n return _compile(\n ^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 1110, in _compile\n raise InternalTorchDynamoError(\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 1059, in _compile\n guarded_code = compile_inner(code, one_graph, hooks, transform)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_utils_internal.py\", line 97, in wrapper_function\n return function(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 761, in compile_inner\n return _compile_inner(code, one_graph, hooks, transform)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 797, in _compile_inner\n out_code = transform_code_object(code, transform)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/bytecode_transformation.py\", line 1422, in transform_code_object\n transformations(instructions, code_options)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 257, in _fn\n return fn(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/convert_frame.py\", line 715, in transform\n tracer.run()\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3500, in run\n super().run()\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1337, in run\n while self.step():\n ^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1246, in step\n self.dispatch_table[inst.opcode](self, inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 819, in wrapper\n return inner_fn(self, inst)\n ^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2933, in CALL\n self._call(inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2927, in _call\n self.call_function(fn, args, kwargs)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1170, in call_function\n self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/lazy.py\", line 201, in realize_and_forward\n return getattr(self.realize(), name)(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/nn_module.py\", line 952, in call_function\n return variables.UserFunctionVariable(fn, source=source).call_function(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py\", line 404, in call_function\n return super().call_function(tx, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py\", line 185, in call_function\n return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1187, in inline_user_function_return\n return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3726, in inline_call\n return tracer.inline_call_()\n ^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3905, in inline_call_\n self.run()\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1337, in run\n while self.step():\n ^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1246, in step\n self.dispatch_table[inst.opcode](self, inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 819, in wrapper\n return inner_fn(self, inst)\n ^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2933, in CALL\n self._call(inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2927, in _call\n self.call_function(fn, args, kwargs)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1170, in call_function\n self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py\", line 185, in call_function\n return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1187, in inline_user_function_return\n return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3726, in inline_call\n return tracer.inline_call_()\n ^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3905, in inline_call_\n self.run()\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1337, in run\n while self.step():\n ^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1246, in step\n self.dispatch_table[inst.opcode](self, inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 819, in wrapper\n return inner_fn(self, inst)\n ^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2933, in CALL\n self._call(inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 2927, in _call\n self.call_function(fn, args, kwargs)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1170, in call_function\n self.push(fn.call_function(self, args, kwargs)) # type: ignore[arg-type]\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py\", line 404, in call_function\n return super().call_function(tx, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/variables/functions.py\", line 185, in call_function\n return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1187, in inline_user_function_return\n return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3726, in inline_call\n return tracer.inline_call_()\n ^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 3905, in inline_call_\n self.run()\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1337, in run\n while self.step():\n ^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1246, in step\n self.dispatch_table[inst.opcode](self, inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1496, in LOAD_GLOBAL\n self._load_global(inst)\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 4052, in _load_global\n _, fglobals_vt, global_source = self.get_globals_source_and_value(name)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 4023, in get_globals_source_and_value\n module_source = self.import_source(module_name)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/utils/_functools.py\", line 40, in wrap\n value = f(self, *args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 1531, in import_source\n value = _import_module(module_name)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/site-packages/torch/_dynamo/symbolic_convert.py\", line 198, in _import_module\n return importlib.import_module(name)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"[environment-path]/lib/python3.11/importlib/__init__.py\", line 126, in import_module\n return _bootstrap._gcd_import(name[level:], package, level)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"\", line 1204, in _gcd_import\n File \"\", line 1176, in _find_and_load\n File \"\", line 1140, in _find_and_load_unlocked\ntorch._dynamo.exc.InternalTorchDynamoError: ModuleNotFoundError: No module named 'moss_benchmark_student'\n", "peak_allocated_gib": 6.937185287475586, "peak_reserved_gib": 6.970703125}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/7c3c63a1b4f9be0ab263.png", "record": {"variant": "int8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "load_seconds": 1.3078781203366816, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_01_anime_woman", "started_at": "2026-10-21T17:15:36.020647+00:00", "finished_at": "2026-10-21T17:17:33.662440+00:00", "prompt_sha256": "0b3d71d7d3d058817658c50227f3fd766bd3d660bebe1e0545eb9e7064cd2289", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.5914453309960663, "seconds_inference": 117.37516023311764, "seconds_including_png": 117.6417978941463, "peak_allocated_gib": 8.546467781066895, "peak_reserved_gib": 11.23046875, "actual_steps": 50, "image": "./results/int8wo-core_compile_style_01_anime_woman_1024x1024_50s_42_0.png", "image_sha256": "6d462d8f9877c14982fafc7907a6e4e93b724ce198c21ac5879f6b2cd74f4137"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/8c5bf4848d82a402eb68.png", "record": {"variant": "int8wo-core", "mode": "compile", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "load_seconds": 1.3078781203366816, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.470468997955322, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:17:33.830677+00:00", "finished_at": "2026-10-21T17:19:27.543720+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": false, "encode_seconds_separate": 2.5598394251428545, "seconds_inference": 113.43911435781047, "seconds_including_png": 113.71304285991937, "peak_allocated_gib": 8.546223640441895, "peak_reserved_gib": 11.23046875, "actual_steps": 50, "image": "./results/int8wo-core_compile_style_02_river_bakery_1024x1024_50s_42_0.png", "image_sha256": "2439972a6a16e0e93ce78911fe8b87a3c6ce43d933e716e6b3e1ecc95026b95d"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/75582a8adac47f46b134.png", "record": {"variant": "bf16-original", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cpu", "encoder_torch": "2.10.0+cu128", "encoder_inference_mode": false, "conditioning_sha256": "a3cd376ff115696ead96075b141961a4737cc488be83637b5af7d1aa7820ff65", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 15.216827714350075, "linear_weight_types": {"Parameter": 269}, "packed_linears": 0, "resident_allocated_gib": 9.467047214508057, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:49:47.757992+00:00", "finished_at": "2026-10-21T17:52:19.829083+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 1.1287592169828713, "seconds_inference": 151.86945568723604, "diffusion_seconds": 151.0236875708215, "decode_seconds": 0.8285387363284826, "png_seconds": 0.20163163961842656, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 152.07108786795288, "peak_allocated_gib": 12.544709205627441, "peak_reserved_gib": 14.595703125, "actual_steps": 50, "image": "./results/bf16-original_eager-sft-float32-torch2.10.0-conda3cd376f_style_02_river_bakery_1024x1024_50s_42_0.png", "image_sha256": "3c6e2f683d2dad26a42db0330152a5895c25621eab067fc416eb1d67af3cbfd0"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/089046b4ad2796822025.png", "record": {"variant": "bf16-original", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.10.0", "torchao": "0.15.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cuda", "encoder_torch": "2.7.0+cu128", "encoder_inference_mode": true, "conditioning_sha256": "a7373c4b242c3c1c11851788004b44e897726c324b346b75bd7ebf2b87c017c6", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 1.9200606187805533, "linear_weight_types": {"Parameter": 269}, "packed_linears": 0, "resident_allocated_gib": 9.467047214508057, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T17:52:29.060777+00:00", "finished_at": "2026-10-21T17:55:00.755510+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.576929251663387, "seconds_inference": 151.49238145537674, "diffusion_seconds": 150.85288301529363, "decode_seconds": 0.6262795496731997, "png_seconds": 0.20235629566013813, "negative_encode_seconds_cold": 5.800361311994493, "seconds_including_png": 151.69473827211186, "peak_allocated_gib": 12.544709205627441, "peak_reserved_gib": 14.595703125, "actual_steps": 50, "image": "./results/bf16-original_eager-sft-float32-torch2.10.0-conda7373c4b_style_02_river_bakery_1024x1024_50s_42_0.png", "image_sha256": "38f72de559b27530ff0f0c49884817f2c850a884acc8284b3fe038c71e956836"}} +{"source_file": "results/measurements.jsonl", "image_file": "runs/moss-image-20261021/quality/images/f209e13ca8fa21356d77.png", "record": {"variant": "fp8wo-core", "mode": "eager", "source_revision": "fc5de0d56fc910cbca6f6625a70f5f582b26deb1", "gpu": "NVIDIA GeForce RTX 5060 Ti", "sm": [12, 0], "versions": {"torch": "2.7.0+cu128", "torchao": "0.12.0", "diffusers": "0.38.0", "transformers": "5.12.1", "accelerate": "1.12.0"}, "encoder": "original_bf16", "timing_scope": "cached conditioning; diffusion + VAE + PNG", "encoder_device": "cuda", "encoder_torch": "2.7.0+cu128", "encoder_transformers": "5.12.1", "encoder_inference_mode": true, "conditioning_sha256": "a7373c4b242c3c1c11851788004b44e897726c324b346b75bd7ebf2b87c017c6", "steps": 50, "cfg": 3.0, "seed": 42, "width": 1024, "height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 3.680873652920127, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T18:06:38.804243+00:00", "finished_at": "2026-10-21T18:09:39.350441+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 2.576929251663387, "seconds_inference": 180.21697008330375, "diffusion_seconds": 179.4678654363379, "decode_seconds": 0.6913340520113707, "png_seconds": 0.3292376520112157, "negative_encode_seconds_cold": 5.800361311994493, "seconds_including_png": 180.54620848642662, "peak_allocated_gib": 8.539727210998535, "peak_reserved_gib": 11.662109375, "actual_steps": 50, 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"height": 1024, "noise_dtype": "float32", "student": null, "compile_dynamic": false, "compute_override": null, "load_seconds": 1.540050976909697, "linear_weight_types": {"Parameter": 41, "AffineQuantizedTensor": 228}, "packed_linears": 228, "resident_allocated_gib": 5.463728427886963, "vae_dtype": "torch.float32", "vae_tiling": false, "status": "ok", "case": "style_02_river_bakery", "started_at": "2026-10-21T18:09:51.908176+00:00", "finished_at": "2026-10-21T18:12:52.225230+00:00", "prompt_sha256": "a1e35ff0061c157c623546255044dc6e77cbb03b3c51152a0c4dc639349f19ad", "repeat": 0, "first_in_process": true, "encode_seconds_separate": 1.1287592169828713, "seconds_inference": 180.0422252737917, "diffusion_seconds": 179.400263692718, "decode_seconds": 0.6248344229534268, "png_seconds": 0.27483265521004796, "negative_encode_seconds_cold": 0.6952687790617347, "seconds_including_png": 180.31705896090716, "peak_allocated_gib": 8.539727210998535, "peak_reserved_gib": 11.662109375, "actual_steps": 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