Instructions to use FastVideo/FastH3-Omni-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FastVideo/FastH3-Omni-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FastVideo/FastH3-Omni-MLX --local-dir FastH3-Omni-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from FastVideo/FastH3-Omni-MLX: direct link, hf CLI and curl.
- Browser
- Download file 1.26 kB
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https://huggingface.co/FastVideo/FastH3-Omni-MLX/resolve/main/README.md
- Command line
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hf download hf://FastVideo/FastH3-Omni-MLX/README.md
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curl -L -o README.md https://huggingface.co/FastVideo/FastH3-Omni-MLX/resolve/main/README.md
1.26 kB
| license: other | |
| license_name: minimax-h3-community-license-agreement | |
| license_link: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE | |
| base_model: FastVideo/FastVideo-FastH3-Omni-8-Step-V1 | |
| tags: [mlx, apple-silicon, fastvideo, minimax-h3, fasth3-omni, benchmark] | |
| # FastH3 Omni on Apple Silicon (MLX) — build + benchmark kit | |
| FastH3 Omni (reference-conditioned video + audio) runs natively on Apple Silicon through FastVideo's MLX runtime | |
| ([hao-ai-lab/FastVideo#2000](https://github.com/hao-ai-lab/FastVideo/pull/2000)). | |
| This repository holds the kit, not the weights: | |
| - `bench/prepare_model_dir.sh` builds the MLX model directory from the public releases | |
| (`FastVideo/FastVideo-FastH3-Omni-8-Step-V1`, `FastVideo/FastH3-Omni-NVFP4-QAD`, `FastVideo/FastH3-NVFP4-VAE-Decoder`, | |
| `lightx2v/LightVAE`) at pinned revisions: INT6 (default), INT8 or BF16 transformer, NVFP4 text-encoder cache, | |
| FastH3 36L/8L decoders and the LightVAE Lite H3 reference encoder. It verifies every file against SHA-256. | |
| - `bench/run_matrix.py` runs the FastH3 Omni reference workloads and writes a latency table. See `bench/README.md`. | |
| Licenses: MiniMax-H3 Community License for the model weights; Qwen3-VL and LightVAE are Apache-2.0 (see `bench/licenses/`). | |