[CVPR 2025 Highlight] Timestep Embedding Tells: It’s Time to Cache for Video Diffusion Model
1University of Chinese Academy of Sciences,
2Alibaba Group
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.
- [2025/04/14] 🔥 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
ComfyUI
Parallelism
Engine
🎉 Supported Models
Text to Video
Image to Video
Video 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 and Wan2.1. 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 and Wan2.1, 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}
}