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

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LongCat recipes

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LongCat inference recipes

LongCat Video from Meituan covers text-to-video and image-to-video, and its maintained examples chain optional distilled and 720p refinement passes.

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

Choose a model and GPU count

Choose a model, then pick a GPU count. Each selection maps to one checked-in recipe. If that recipe does not use your chosen count, the page says so instead of guessing.

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        <span class="cookbook-badge" data-cookbook-evidence>Source-backed</span>
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      <a data-cookbook-source href="../../inference/examples/basic/">Open example source</a>
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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

• Each LongCat script runs multiple passes (basic, distilled, refine); total runtime scales accordingly, and every pass prints its own output directory.
• Out of memory: the sources already enable VAE and text-encoder CPU offload; further options are covered in Offloading.

Evidence status

All recipes on this page are Source-backed: their commands, model IDs, and flags were validated against the checked-in FastVideo sources listed above (static validation). No runtime GPU validation is recorded for these recipes, so GPU model fit, memory use, throughput, and runtime duration are Unknown and deliberately not claimed. Runtime buttons show only the GPU counts configured in checked-in sources.