Buckets:
| # Models | |
| All models are on Hugging Face under [txgsync](https://huggingface.co/txgsync). Each model card has the full results, | |
| the generation checks and the known issues. | |
| ## Lineage | |
| ``` | |
| IFM/K2-Horizon-MoVA-36B-A4B original (GQA) | |
| ├─ K2-Horizon-MoVA-36B-A4B-NSLM-p4mx-q4v seeded experts, 22.76 GB | |
| └─ K2-Horizon-MoVA-36B-A4B-MLA TransMLA conversion + distillation heal, BF16 | |
| ├─ K2-Horizon-MoVA-36B-A4B-MLA-NanoSeedLM-P4 seeds, 22.20 GB | |
| ├─ K2-Horizon-MoVA-36B-A4B-MLA-NanoSeedLM-P3 seeds, 20.07 GB | |
| ├─ K2-Horizon-MoVA-36B-A4B-MLA-oQ4e affine (oMLX oQ), 22.89 GB | |
| ├─ K2-Horizon-MoVA-36B-A4B-MLA-oQ6e affine (oMLX oQ), 31.74 GB | |
| └─ K2-Horizon-MoVA-36B-A4B-MLA-oQ8e affine (oMLX oQ), 40.61 GB | |
| IFM/K2-Horizon-0.9B original (dense) | |
| └─ K2-Horizon-0.9B-NSLM-seeds-4bpw seeds, 0.54 GB | |
| Qwen/Qwen3.8-Flash-Next original (qwen4_exp) | |
| └─ mlx-community/Qwen3.8-Flash-Next-4bit-mtp MLX 4-bit (group 32), with the MTP head | |
| ├─ Qwen3.8-Flash-Next-NanoSeedLM-P4 seed experts (P = 4), the rest as the 4-bit model, 105.7 GB | |
| └─ Qwen3.8-Flash-Next-NanoSeedLM-P3 seed experts (P = 3), the rest as the 4-bit model, 98.2 GB | |
| ``` | |
| The oQe models are for comparison. They let us compare seeds with a calibrated affine quantization of the same MLA | |
| model. | |
| ## Runtimes | |
| | Model | Loader | oMLX | Metal engine | CUDA engine | | |
| |---|---|---|---|---| | |
| | [NSLM-p4mx-q4v](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-NSLM-p4mx-q4v) | `nanoseedlm_k2.py` | Yes | Yes | Yes | | |
| | [MLA-NanoSeedLM-P4](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA-NanoSeedLM-P4) | `nanoseedlm_k2.py` | Yes | Yes | Not checked | | |
| | [MLA-NanoSeedLM-P3](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA-NanoSeedLM-P3) | `nanoseedlm_k2.py` | Yes | Yes | Not yet (P = 3 tensors) | | |
| | [MLA](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA) (BF16) | `k2_mla.py` | Yes | Not checked | Not checked | | |
| | [MLA-oQ4e](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA-oQ4e), [oQ6e](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA-oQ6e), [oQ8e](https://huggingface.co/txgsync/K2-Horizon-MoVA-36B-A4B-MLA-oQ8e) | `k2_mla.py` | Yes | No | No | | |
| | [0.9B-NSLM-seeds-4bpw](https://huggingface.co/txgsync/K2-Horizon-0.9B-NSLM-seeds-4bpw) | `nanoseedlm_k2.py` | Yes | No | No | | |
| | [Qwen3.8-Flash-Next-NanoSeedLM-P4](https://huggingface.co/txgsync/Qwen3.8-Flash-Next-NanoSeedLM-P4), [P3](https://huggingface.co/txgsync/Qwen3.8-Flash-Next-NanoSeedLM-P3) | `nanoseedlm_qwen4.py` (mlx-vlm) | Not yet | No | Yes (`nslm-qwen4-gen`) | | |
| oMLX removes `model_file` from `qwen4_exp` configurations, so it does not load the Qwen3.8-Flash-Next loader yet. | |
| Use mlx-vlm 0.7.12 or later with `--trust-remote-code`. To use a model in oMLX, read [The MLX loader](../guides/mlx.md). | |
| To use a model in the engine, read [Run and serve](../guides/run-and-serve.md). | |
| ## Which model to choose | |
| - **For the longest context on a Mac:** MLA-NanoSeedLM-P4 or MLA-NanoSeedLM-P3 in oMLX. | |
| - **For the quality nearest to the original:** NSLM-p4mx-q4v. It keeps the original attention. | |
| - **For a small download to test the seed format:** K2-Horizon-0.9B-NSLM-seeds-4bpw. Its quality is lower than | |
| IFM's Q4_K_M, and it is slower. | |
| - **To try seed experts on Qwen3.8-Flash-Next:** Qwen3.8-Flash-Next-NanoSeedLM-P4 or -P3, in mlx-vlm or with | |
| `nslm-qwen4-gen` on CUDA. Against the 4-bit MLX model, P4 agrees on the top token 91.9% of the time. KL divergence | |
| against BF16 is not measured yet. | |
| - **For daily use with no interest in seeds:** an affine quantization of the original model. | |
| ## Related data | |
| - [BF16 reference log-probs](https://huggingface.co/datasets/txgsync/K2-Horizon-MoVA-36B-A4B-bf16-ref-logprobs), for | |
| `nslm-mova-score`. | |
| - [Seed bank](https://huggingface.co/datasets/txgsync/K2-Horizon-MoVA-36B-A4B-NSLM-seedbank), the searched seed blocks. | |
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