Initial export: 2619 compatibility verdicts, 946 recipes, 97 models, 27 GPUs

README.md

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+---
+pretty_name: Self-Hosted AI — GPU Compatibility, Recipes and Catalogue
+license: cc-by-sa-4.0
+language:
+  - en
+size_categories:
+  - 1K<n<10K
+task_categories:
+  - table-question-answering
+  - text-retrieval
+tags:
+  - gpu
+  - vram
+  - local-llm
+  - quantization
+  - hardware-compatibility
+  - self-hosted
+configs:
+  - config_name: compatibility
+    default: true
+    data_files: data/compatibility.parquet
+  - config_name: recipes
+    data_files: data/recipes.parquet
+  - config_name: models
+    data_files: data/models.parquet
+  - config_name: gpus
+    data_files: data/gpus.parquet
+  - config_name: benchmark_sources
+    data_files: data/benchmark_sources.parquet
+---
+
+# Self-Hosted AI — GPU Compatibility, Recipes and Catalogue
+
+Which open-weight AI models actually run on which consumer GPU, and what it takes
+to get them running. 2 619 model×GPU verdicts across 97 models
+and 27 cards, plus 946 full setup guides
+(16 MB of markdown) written against specific hardware.
+
+This is the machine-readable form of [smeltcore.com](https://smeltcore.com). Every row carries a
+`url` back to the page it came from.
+
+Generated 2026-08-18T11:25:50+00:00 from the public read API (`https://api.smeltcore.com/api/v1`) — no private data, no
+credentials, reproducible by anyone.
+
+## Configs
+
+| config | rows | what it is |
+|---|---:|---|
+| `compatibility` | 2 619 | **the point of the dataset.** One row per model × GPU, with a verdict |
+| `recipes` | 946 | full setup guides, markdown included, tagged by model / GPU / tool |
+| `models` | 97 | the catalogue: licence, upstream repo, modality |
+| `gpus` | 27 | the cards: VRAM, vendor, series |
+| `benchmark_sources` | 157 | third-party measurements, normalised and cited |
+
+```python
+from datasets import load_dataset
+
+compat = load_dataset("REPO_ID", "compatibility", split="train")
+compat.filter(lambda r: r["gpu_slug"] == "rtx-4090" and r["fit"] == "verified")
+```
+
+## The `fit` scale
+
+The whole dataset turns on this column, so it is worth reading before using it.
+
+| verdict | rows | meaning |
+|---|---:|---|
+| `verified` | 945 | somebody ran it on this exact card and wrote down how — there is a recipe behind the row |
+| `fits` | 663 | inferred: the model's memory floor is under the card's VRAM, and the vendor is supported. Not measured |
+| `unknown` | 455 | no floor established for this model, so no honest call can be made |
+| `too_big` | 556 | the memory floor exceeds this card. This is the one verdict asserted from anywhere, not only from same-vendor evidence |
+
+The asymmetry between `fits` and `too_big` is deliberate: a model is only called
+runnable on evidence from the same vendor's hardware, but it is called *not*
+runnable from a memory floor established anywhere. Being wrong in the optimistic
+direction wastes somebody's evening; being wrong in the pessimistic direction
+only costs them a model they could have tried.
+
+`min_vram_gb` is a **filter floor in decimal GB** — the smallest card the model is
+offered on — not a measured peak. Measured peaks, where they exist, are in
+`peak_vram_gb` and in `benchmark_sources`.
+
+## Provenance, stated plainly
+
+**`recipes` is first-party.** Written for this catalogue against named hardware,
+with the quantization, runtime and settings each one was written for.
+
+**`benchmark_sources` is not.** 111 of 157 rows come from a
+single third-party site (`www.hardware-corner.net`), and 4 were measured by us.
+It is published as a **citation index, not as our benchmarks**: what this project
+contributes is the normalisation — one model slug, one GPU slug, one unit
+convention — and every row is required to carry `source_url` back to whoever did
+the measuring. Credit and verification both belong there. If you use a number from
+this table, cite the source row, not this dataset.
+
+`confidence` is a 0–1 score reflecting how much the source is trusted; it is not a
+statistical confidence interval.
+
+## Coverage and what it is not
+
+- 27 consumer cards — NVIDIA, AMD and Apple silicon. **No datacenter GPUs**
+  (no H100, no A100): this catalogue is about hardware people own.
+- 8 modalities: llm (37), multimodal (18), image (14), video (14), tts (6), 3d (4), music (2), specialized (2).
+- Verdicts are about **whether it runs**, not how well it performs. There is no
+  quality benchmark here and no leaderboard.
+- The catalogue moves — models get added, quantizations appear weekly. A stale copy
+  of this dataset will understate coverage. `generated_at` above is the only date
+  that matters.
+
+## Licence and attribution
+
+Released under **CC BY-SA 4.0**, matching the licence the site publishes its data
+under. Attribution goes to [smeltcore.com](https://smeltcore.com).
+
+Rows in `benchmark_sources` describe third-party work; that licence does not
+extend to the measurements themselves, which belong to the sites named in
+`source_url`.
+
+## Citation
+
+```bibtex
+@misc{smeltcore_selfhosted_ai,
+  title  = {Self-Hosted AI — GPU Compatibility, Recipes and Catalogue},
+  author = {smeltcore},
+  url    = {https://smeltcore.com},
+  note   = {Generated 2026-08-18T11:25:50+00:00},
+  year   = {2026}
+}
+```

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