#1111th of 24 in Image and videoFor image, video and design, video and animation
wan2.2
Open-weight video generation models for text, image, speech and animation
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- Stars
- 18.1k
- License
- Apache-2.0
- Last commit
- Sep 2026
- Language
- Python
14,746 on 31 Mar 202618,071 on 20 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Wan2.2 is Alibaba's video diffusion model family with a generate.py CLI for text-to-video, image-to-video, speech-to-video and character animation. It ships a MoE A14B pair for 480P/720P and a 5B TI2V model at 720P/24fps with a 16x16x4 compression VAE. Weights are on Hugging Face and ModelScope, and multi-GPU inference uses FSDP with DeepSpeed Ulysses.
Who it is for: Researchers and self-hosters generating video with open-weight diffusion models
Strengths
- Covers T2V, I2V, TI2V, speech-to-video and character animation in one repo
- TI2V-5B runs 720P at 24fps on a single 24GB GPU such as an RTX 4090
- Multi-GPU inference with FSDP and DeepSpeed Ulysses is included
- Integrated into ComfyUI and Diffusers, with weights on Hugging Face and ModelScope
Weaknesses
- A14B single-GPU inference needs at least 80GB VRAM
- CLI scripts only; no built-in web UI or server
- Prompt extension needs a Dashscope API key or a local Qwen model
- Requires torch >= 2.4.0 and flash_attn, which can fail to install
What it needs
- GPU required
- Needs PyTorch >= 2.4.0, flash_attn, Dashscope API (optional, prompt extension), CosyVoice (optional, speech-to-video TTS)
- Models: Wan2.2-T2V-A14B, Wan2.2-I2V-A14B, Wan2.2-TI2V-5B, Wan2.2-S2V-14B, Wan2.2-Animate-14B
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