Available as managed deploymentVideoWan-AIImage→video2 variants10k dl/mo
Wan2.1-VACE is an open-weight video model from Wan-AI. AxForge deploys and operates it
for you on dedicated EU-owned hardware — with the licence handled where one is required.
In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features:
👍 SOTA Performance: Wan2.1 consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks.
👍 Supports Consumer-grade GPUs: The T2V-1.3B model requires only 8.19 GB VRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models.
👍 Multiple Tasks: Wan2.1 excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation.
👍 Visual Text Generation: Wan2.1 is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications.
👍 Powerful Video VAE: Wan-VAE delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation.
Apr 17, 2025: 👋 We introduce Wan2.1FLF2V with its inference code and weights!
Mar 21, 2025: 👋 We are excited to announce the release of the Wan2.1technical report. We welcome discussions and feedback!
Mar 3, 2025: 👋 Wan2.1's T2V and I2V have been integrated into Diffusers (T2V | I2V). Feel free to give it a try!
Feb 27, 2025: 👋 Wan2.1 has been integrated into ComfyUI. Enjoy!
Feb 25, 2025: 👋 We've released the inference code and weights of Wan2.1.
Community Works
If your work has improved Wan2.1 and you would like more people to see it, please inform us.
Phantom has developed a unified video generation framework for single and multi-subject references based on Wan2.1-T2V-1.3B. Please refer to their examples.
UniAnimate-DiT, based on Wan2.1-14B-I2V, has trained a Human image animation model and has open-sourced the inference and training code. Feel free to enjoy it!
CFG-Zero enhances Wan2.1 (covering both T2V and I2V models) from the perspective of CFG.
TeaCache now supports Wan2.1 acceleration, capable of increasing speed by approximately 2x. Feel free to give it a try!
DiffSynth-Studio provides more support for Wan2.1, including video-to-video, FP8 quantization, VRAM optimization, LoRA training, and more. Please refer to their examples.
📑 Todo List
Wan2.1 Text-to-Video
[x] Multi-GPU Inference code of the 14B and 1.3B models
[x] Checkpoints of the 14B and 1.3B models
[x] Gradio demo
[x] ComfyUI integration
[x] Diffusers integration
[ ] Diffusers + Multi-GPU Inference
Wan2.1 Image-to-Video
[x] Multi-GPU Inference code of the 14B model
[x] Checkpoints of the 14B model
[x] Gradio demo
[x] ComfyUI integration
[x] Diffusers integration
[ ] Diffusers + Multi-GPU Inference
Wan2.1 First-Last-Frame-to-Video
[x] Multi-GPU Inference code of the 14B model
[x] Checkpoints of the 14B model
[x] Gradio demo
[ ] ComfyUI integration
[x] Diffusers integration
[ ] Diffusers + Multi-GPU Inference
Wan2.1 VACE
[x] Multi-GPU Inference code of the 14B and 1.3B models
[x] Checkpoints of the 14B and 1.3B models
[x] Gradio demo
[x] ComfyUI integration
[x] Diffusers integration
[ ] Diffusers + Multi-GPU Inference
Quickstart
Installation
Clone the repo:
git clone https://github.com/Wan-Video/Wan2.1.git
cd Wan2.1
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Call it like any OpenAI endpoint
Once AxForge deploys wan2-1-vace for you, it answers on the OpenAI-compatible API — the same
base URL and keys as every other model. (wan2-1-vace below is illustrative; you get the exact
model name on deployment.)