hao-ai-lab-FastVideo/docs/cookbook/wan.md

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Wan recipes

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Wan inference recipes

Wan recipes span maintained CUDA examples and the released FastMetal 1.3B, 5B, and 14B native MLX paths for Apple Silicon.

7 maintained recipes

Inference live Distillation planned Fine-tuning planned Training planned Evaluation planned Optimization planned Deployment planned

Pick a recipe and runtime

Choose the result you want, then use a maintained CUDA or native MLX path.

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Before you run

The generated commands expect a local clone:

git clone https://github.com/hao-ai-lab/FastVideo.git
cd FastVideo

Use Configuration for supported Python and CLI settings, Optimizations for attention and memory tradeoffs, and the support matrix for the supported model and optimization surface.

Troubleshooting

• Out of memory on the A14B recipes: the checked-in sources already enable CPU offload; see Configuration for the offload surface before reducing resolution or frames.
• The FastWan2.1 recipe requires VIDEO_SPARSE_ATTN; confirm the environment variable in the command was set in the same shell.
• Gated or missing checkpoints: run huggingface-cli login and confirm you accepted the model's license on Hugging Face.

Evidence status

Every recipe on this page maps to a checked-in FastVideo source. The FastMetal MLX releases include the recorded M4 Max system memory, documented unified-memory floor, and measured peak MLX memory. CUDA entries remain Source-backed where the examples record a GPU count but no exact GPU model or VRAM. Unlisted hardware is unknown, not unsupported.