Causal Wan 2.2

CausalWan2.2 is a FastVideo-released 14B MoE causal-diffusion variant of Wan 2.2 with 8-step inference.

Teaser video generated with the FlashDreams Causal Wan2.2 integration.

This integration uses flashdreams-run-v2.

Quick Start

T2V

uv sync --package flashdreams-fastvideo-causal-wan22 --inexact
uv run --no-sync flashdreams-run-v2 \
  t2v-fastvideo-causal-wan2.2-t2v-14b \
  --output-path artifacts/causal-wan22.mp4 --timeout unbound -- \
  --prompt "A cat surfing" --total-blocks 7

Demo Presets Demo Arguments

Demo Presets

T2V

Preset	Description
`t2v-fastvideo-causal-wan2.2-t2v-14b`	FastVideo CausalWan 2.2 14B MoE T2V with the Wan VAE decoder and eight denoising steps.

Developer Details

Integration Source Pipeline configurations

Minimum VRAM: about 112 GB.
PyTorch: 2.9 or newer.

Samples

prompt: "A stylish woman strolls down a bustling Tokyo street, the warm glow of neon lights and animated city signs casting vibrant reflections. She wears a sleek black leather jacket paired with a flowing red dress and black boots, her black purse slung over her shoulder. Sunglasses perched on her nose and a bold red lipstick add to her confident, casual demeanor. The street is damp and reflective, creating a mirror-like effect that enhances the colorful lights and shadows. Pedestrians move about, adding to the lively atmosphere. The scene is captured in a dynamic medium shot with the woman walking slightly to one side, highlighting her graceful strides."

prompt: "A playful raccoon is seen playing an electronic guitar, strumming the strings with its front paws. The raccoon has distinctive black facial markings and a bushy tail. It sits comfortably on a small stool, its body slightly tilted as it focuses intently on the instrument. The setting is a cozy, dimly lit room with vintage posters on the walls, adding a retro vibe. The raccoon's expressive eyes convey a sense of joy and concentration. Medium close-up shot, focusing on the raccoon's face and hands interacting with the guitar."

Citation

FastVideo lists the following research citations:

@article{zhang2025fast,
  title={Fast video generation with sliding tile attention},
  author={Zhang, Peiyuan and Chen, Yongqi and Su, Runlong and Ding, Hangliang and Stoica, Ion and Liu, Zhengzhong and Zhang, Hao},
  journal={arXiv preprint arXiv:2502.04507},
  year={2025}
}

@article{zhang2025vsa,
  title={Vsa: Faster video diffusion with trainable sparse attention},
  author={Zhang, Peiyuan and Chen, Yongqi and Huang, Haofeng and Lin, Will and Liu, Zhengzhong and Stoica, Ion and Xing, Eric and Zhang, Hao},
  journal={arXiv preprint arXiv:2505.13389},
  year={2025}
}