Wan 2.2
Alibaba’s open-weight video generation models (text, image and speech to video).
- Stars
- 17.9K
- Forks
- 2.3K
- Open issues
- 318
- Last commit
- 2026-09-21
Live from the GitHub API · updated 2026-10-15
What is Wan 2.2?
Wan 2.2 is Alibaba’s open video model family under Apache 2.0. It includes large Mixture-of-Experts text-to-video and image-to-video models and a compact 5B text+image-to-video model that runs on a single consumer GPU, plus ComfyUI and Diffusers integrations.
Key features
- Text-to-video and image-to-video at 480p/720p
- TI2V-5B model fits a 24 GB consumer GPU
- Mixture-of-Experts A14B models for higher quality
- ComfyUI and Diffusers support
System requirements
- Platforms
- Linux · Windows
- GPU
- NVIDIA
- VRAM
- 24 GB for TI2V-5B at 720p; 80 GB-class GPUs (or offloading) for A14B models
- Python
- 3.10+
How to install Wan 2.2
Summarized from the project’s README. Projects change quickly — check the GitHub page for the latest instructions.
Reference code
- 1Clone and install (PyTorch ≥ 2.4).
git clone https://github.com/Wan-Video/Wan2.2.git cd Wan2.2 pip install -r requirements.txt - 2Download a model from Hugging Face.
huggingface-cli download Wan-AI/Wan2.2-TI2V-5B --local-dir ./Wan2.2-TI2V-5B - 3Generate a clip.
python generate.py --task ti2v-5B --size 1280*704 --ckpt_dir ./Wan2.2-TI2V-5B --offload_model True --convert_model_dtype --t5_cpu --prompt "A cat surfing at sunset"
ComfyUI
- 1Update ComfyUI and open the Wan 2.2 workflow from the built-in templates; it lists the model files to download.
Strengths
- Best open-weight video quality class
- Apache 2.0 license
- Runs locally
Limitations
- Large models need data-center GPUs
- Slow on consumer hardware
Wan 2.2 alternatives compared
| Software | Stars | License | Platforms | VRAM |
|---|---|---|---|---|
| Wan 2.2 Alibaba’s open-weight video generation models (text, image and speech to video). | 17.9K | Apache-2.0 | 24 GB for TI2V-5B at 720p; 80 GB-class GPUs (or offloading) for A14B models | |
| HunyuanVideo Tencent’s 13B-parameter open video foundation model. | 12.6K | Tencent Hunyuan Community License | 45 GB minimum, 60–80 GB recommended for 720p (per README); less with community quantizations | |
| LTX-Video Fast, real-time-capable open video generation from Lightricks. | 11.1K | Apache-2.0 | 12 GB+ for smaller variants; more for 13B models | |
| CogVideoX Open text-to-video and image-to-video models from Zhipu AI / Tsinghua. | 13.1K | Apache-2.0 | ~12–24 GB depending on model and optimizations (see the README table) | |
| FramePack Long image-to-video generation on laptop GPUs with as little as 6 GB VRAM. | 17.3K | Apache-2.0 | 6 GB minimum | |
| AnimateDiff Animate your Stable Diffusion checkpoints with plug-in motion modules. | 12.3K | Apache-2.0 | 8–12 GB |
Related models
FAQ
Is Wan 2.2 free?
Yes — Wan 2.2 is open-source software released under the Apache-2.0 license. Check the license (and any model weight licenses) before commercial use.
Does Wan 2.2 run on Windows, Mac and Linux?
Wan 2.2 supports: Linux, Windows.
What hardware do I need for Wan 2.2?
NVIDIA. VRAM: 24 GB for TI2V-5B at 720p; 80 GB-class GPUs (or offloading) for A14B models
How do I install Wan 2.2?
1. Clone and install (PyTorch ≥ 2.4). 2. Download a model from Hugging Face. 3. Generate a clip.
What are the best Wan 2.2 alternatives?
Popular alternatives include HunyuanVideo, LTX-Video, CogVideoX, FramePack. See the comparison table on this page.
Can I use Wan 2.2 online without installing it?
If you don’t have a large GPU, AiLoft runs Veo 3.1 and Kling 2.5 in the cloud — generate and compare clips in the browser.
No 24 GB GPU? Generate AI video online
Run Veo 3.1 and Kling 2.5 in the cloud and compare clips side by side — pay per clip.