Wan 2.2
Alibaba (Tongyi Lab)
MoE architecture with 27B total params but only 14B active. Trained on 65% more images and 83% more video than 2.1. Outperforms leading closed-source models on Wan-Bench 2.0.
Wan 2.1
Alibaba (Tongyi Lab)
The foundation that started it all. 1.3B variant runs on virtually any GPU. First open model to beat closed-source across benchmarks.
Pick Wan 2.2 if…
You want cinematic style control, speech-to-video, or consumer GPU deployment (TI2V-5B).
Pick Wan 2.1 if…
You want consumer GPU workflows, academic research, or Chinese + English text-in-video.
Specifications
Strengths & Trade-offs
Wan 2.2
Strengths
- +First MoE in video diffusion
- +27B total but only 14B active per step
- +high-noise expert for layout + low-noise for detail
- ++65.6% more images and +83.2% more video training data vs 2.1
- +cinematic aesthetic control (lighting, composition, contrast, color tone)
Trade-offs
- -720p cap
- -MoE needs careful threshold tuning (SNR-based)
- -no native audio in base model (S2V is separate)
- -newer ecosystem than 2.1
Best For
- →Self-hosted production
- →cinematic style control
- →speech-to-video
- →consumer GPU deployment (TI2V-5B)
Wan 2.1
Strengths
- +SOTA open-source at launch
- +1.3B model runs on any consumer GPU (8.19GB VRAM)
- +first video model with Chinese + English text generation
- +Wan-VAE encodes unlimited-length 1080P
- +T2V/I2V/Video Editing/T2I/V2A all supported
Trade-offs
- -720p max
- -5s duration
- -1.3B quality limited
- -no native audio generation
- -superseded by 2.2 on quality
Best For
- →Budget local deployment
- →consumer GPU workflows
- →academic research
- →Chinese + English text-in-video
Run these models on Floyo
Browser-based ComfyUI. No setup, no GPU required.
Wan 2.2 Animate Preprocess (Kijai)
Wan 2.2 + Qwen V2V Restyle
Wan 2.2 T2V with UnifiedRew
Wan 2.2 Animate Character Replacement