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ali-vilab/TeaCache
Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
About ali-vilab/TeaCache
ali-vilab/TeaCache is an open-source project on GitHub, mainly written in Python. Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model It currently holds 1,380 stars and 60 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).
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GitHub Repository Details
README
[CVPR 2025 Highlight] Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
Feng Liu1*,
Shiwei Zhang2†,
Xiaofeng Wang1,3,
Yujie Wei4,
Haonan Qiu5
Yuzhong Zhao1, Yingya Zhang2, Qixiang Ye1, Fang Wan1‡
Yuzhong Zhao1, Yingya Zhang2, Qixiang Ye1, Fang Wan1‡
1University of Chinese Academy of Sciences,
2Alibaba Group
3Institute of Automation, Chinese Academy of Sciences
4Fudan University, 5Nanyang Technological University
3Institute of Automation, Chinese Academy of Sciences
4Fudan University, 5Nanyang Technological University
(* Work was done during internship at Alibaba Group. † Project Leader. ‡ CorresCorresponding author.)
🫖 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.(liufeng20@mails.ucas.ac.cn)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-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.
- 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
🤖 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. (liufeng20@mails.ucas.ac.cn)
📖 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}
}
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