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
TeaCache
ali-vilabApache-2.0长期未更新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
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.mdREADME 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
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
暂无 release 数据(可能没有发版,或尚未同步)。
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
[CVPR 2025 Highlight] Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

🫖 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
- If you like our project, please give us a star ⭐ on GitHub for the latest update.
- [2025/06/08] 🔥 Update coefficients of Lumina-Image-2.0. Thanks @spawner1145.
- [2025/05/26] 🔥 Support Lumina-Image-2.0. Thanks @spawner1145.
- [2025/05/25] 🔥 Support HiDream-I1. Thanks @YunjieYu.
- [2025/04/14] 🔥 Update coefficients of CogVideoX1.5. Thanks @zishen-ucap.
- [2025/04/05] 🎉 Recommended as a highlight in CVPR 2025, top 16.8% in accepted papers and top 3.7% in all papers.
- [2025/03/13] 🔥 Optimized TeaCache for Wan2.1. Thanks @zishen-ucap.
- [2025/03/05] 🔥 Support Wan2.1 for both T2V and I2V.
- [2025/02/27] 🎉 Accepted in CVPR 2025.
- [2025/01/24] 🔥 Support Cosmos for both T2V and I2V. Thanks @zishen-ucap.
- [2025/01/20] 🔥 Support CogVideoX1.5-5B for both T2V and I2V. Thanks @zishen-ucap.
- [2025/01/07] 🔥 Support TangoFlux. TeaCache works well for Audio Diffusion Models!
- [2024/12/30] 🔥 Support Mochi and LTX-Video for Video Diffusion Models. Support Lumina-T2X for Image Diffusion Models.
- [2024/12/27] 🔥 Support FLUX. TeaCache works well for Image Diffusion Models!
- [2024/12/26] 🔥 Support ConsisID. Thanks @SHYuanBest.
- [2024/12/24] 🔥 Support HunyuanVideo.
- [2024/12/19] 🔥 Support CogVideoX.
- [2024/12/06] 🎉 Release the code of TeaCache. Support Open-Sora, Open-Sora-Plan and Latte.
- [2024/11/28] 🎉 Release the paper of TeaCache.
🧩 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
- FramePack supports TeaCache. Thanks @lllyasviel.
- FastVideo supports TeaCache. Thanks @BrianChen1129 and @jzhang38.
- EasyAnimate supports TeaCache. Thanks @hkunzhe and @bubbliiiing.
- Ruyi-Models supports TeaCache. Thanks @cellzero.
- ConsisID supports TeaCache. Thanks @SHYuanBest.
ComfyUI
- ComfyUI-TeaCache for TeaCache. Thanks @YunjieYu.
- ComfyUI-WanVideoWrapper supports TeaCache4Wan2.1. Thanks @kijai.
- ComfyUI-TangoFlux supports TeaCache. Thanks @LucipherDev.
- ComfyUI_Patches_ll supports TeaCache. Thanks @lldacing.
- Comfyui_TTP_Toolset supports TeaCache. Thanks @TTPlanetPig.
- ComfyUI-TeaCacheHunyuanVideo for TeaCache4HunyuanVideo. Thanks @facok.
- ComfyUI-HunyuanVideoWrapper supports TeaCache4HunyuanVideo. Thanks @kijai, ctf05 and DarioFT.
Parallelism
- Teacache-xDiT for multi-gpu inference. Thanks @MingXiangL.
Engine
- SD.Next supports TeaCache. Thanks @vladmandic.
- DiffSynth Studio supports TeaCache. Thanks @Artiprocher.
🎉 Supported Models
Text to Video
- TeaCache4Wan2.1
- TeaCache4Cosmos
- TeaCache4CogVideoX1.5
- TeaCache4LTX-Video
- TeaCache4Mochi
- TeaCache4HunyuanVideo
- TeaCache4CogVideoX
- TeaCache4Open-Sora
- TeaCache4Open-Sora-Plan
- TeaCache4Latte
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
- The majority of this project is released under the Apache 2.0 license as found in the LICENSE file.
- For 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, please follow their LICENSE.
- The service is a research preview. Please contact us if you find any potential violations. ([email protected])
📖 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}
}