TeaCache

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一种面向视频扩散模型的免训练缓存加速方法,利用时间步嵌入判断哪些步骤可以复用计算结果,从而在不重新训练的情况下显著提升推理速度。

Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

暂无版本1,387star62fork同步于 2026-11-07 07:30 UTC

怎么上手

由 README 提炼,执行前请确认
README 未给出统一安装命令,各模型用法见对应子目录 README,如 TeaCache4Wan2.1/README.md
硬件要求按 README 说明

README 未说明具体显存与 GPU 型号要求,实际需求取决于所接入的扩散模型本身

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项目说明

由 README 自动翻译提炼

免训练缓存加速视频/图像/音频扩散模型推理,用时间步嵌入判断何时复用计算结果

一种面向视频扩散模型的免训练缓存加速方法,利用时间步嵌入判断哪些步骤可以复用计算结果,从而在不重新训练的情况下显著提升推理速度。

核心能力

  • 用时间步嵌入估计相邻步输出差异,决定是否跳过计算
  • 无需训练,直接接入已有扩散模型推理流程
  • 覆盖视频、图像、音频三类扩散模型
  • 已适配 Wan2.1、HunyuanVideo、CogVideoX、FLUX 等主流模型
  • 提供各模型专用系数,可按模型结构迁移复用

容易踩的坑

各模型需进入对应子目录按其 README 单独配置,没有统一入口;需自行准备所接入模型的权重与依赖环境;换用新模型时需重新标定或迁移 rescaling 系数,否则加速效果与画质可能不达预期

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    README 原文

    未翻译

    [CVPR 2025 Highlight] Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

    hf_paper arXiv Home Page License github

    visualization

    🫖 Introduction

    We introduce Timestep Embedding Aware Cache (TeaCache), a training-free caching approach that estimates and leverages the fluctuating differences among model outputs across timesteps, thereby accelerating the inference. TeaCache works well for Video Diffusion Models, Image Diffusion models and Audio Diffusion Models. For more details and results, please visit our project page.

    🔥 Latest News

    🧩 Community Contributions

    If you develop/use TeaCache in your projects and you would like more people to see it, please inform us.([email protected])

    Model

    ComfyUI

    Parallelism

    Engine

    🎉 Supported Models

    Text to Video

    Image to Video

    Text to Image

    Text to Audio

    🤖 Instructions for Supporting Other Models

    • Welcome for PRs to support other models.
    • If the custom model is based on or has similar model structure to the models we've supported, you can try to directly transfer TeaCache to the custom model. For example, rescaling coefficients for CogVideoX-5B can be directly applied to CogVideoX1.5, ConsisID and rescaling coefficients for FLUX can be directly applied to TangoFlux.
    • Otherwise, you can refer to these successful attempts, e.g., 1, 2.

    💐 Acknowledgement

    This repository is built based on VideoSys, Diffusers, Open-Sora, Open-Sora-Plan, Latte, CogVideoX, HunyuanVideo, ConsisID, FLUX, Mochi, LTX-Video, Lumina-T2X, TangoFlux, Cosmos, Wan2.1, HiDream-I1 and Lumina-Image-2.0. Thanks for their contributions!

    🔒 License

    📖 Citation

    If you find TeaCache is useful in your research or applications, please consider giving us a star ⭐ and citing it by the following BibTeX entry.

    @article{liu2024timestep,
      title={Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model},
      author={Liu, Feng and Zhang, Shiwei and Wang, Xiaofeng and Wei, Yujie and Qiu, Haonan and Zhao, Yuzhong and Zhang, Yingya and Ye, Qixiang and Wan, Fang},
      journal={arXiv preprint arXiv:2411.19108},
      year={2024}
    }