Model reference · open weights
Wan2.2-S2V is an open-weight video model from FastVideo. Wan2.2-S2V-14B-Diffusers (BF16) weighs 57.1 GB; the smallest configuration that runs it is L40S 48 GB.
Summary of the FastVideo/Wan2.2-S2V-14B-Diffusers model card, 2026-10-01
What it is
| Released by | FastVideo |
|---|---|
| Released | 2026-08-15 |
| Parameters | 16.3B |
| VRAM | 57.1 GB for the weights |
What it runs on
| Card | Weights | Memory |
|---|---|---|
| RTX 3060 12 GB … RTX 5090 32 GB | does not fit | |
| L40S 48 GB | fits (encoders offloaded) | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
This is Wan-AI/Wan2.2-S2V-14B — a model that animates a picture of a person in sync with a voice recording — repacked into the folder layout that FastVideo loads.
No weights were changed. The video model tensors are byte-identical copies of the official release. The text encoder, VAE, tokenizer and scheduler come from Wan-AI's own Diffusers release of Wan2.1 (the same weights S2V uses), and the wav2vec2 speech encoder is the one bundled inside the official S2V repo.
Made with
scripts/checkpoint_conversion/wan_s2v_to_diffusers.py
from FastVideo PR #1683.
from fastvideo import VideoGenerator
gen = VideoGenerator.from_pretrained("SuhaanCoding/Wan2.2-S2V-14B-Diffusers")
gen.generate_video(
prompt="...",
image_path="face.jpg",
audio_path="speech.wav",
output_path="out.mp4",
save_video=True,
)
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. How to run this model is on its model card.