Model reference · open weights
Wan-Dancer is an open-weight video model from Wan-AI. Wan-Dancer-14B (BF16) weighs 85.6 GB; the smallest configuration that runs it is L40S 48 GB.
Summary of the Wan-AI/Wan-Dancer-14B model card, 2026-10-01
What it is
| Released by | Wan-AI |
|---|---|
| Released | 2026-07-10 |
| VRAM | 85.6 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 (encoders offloaded) | 78.2 GB |
| H100 80 GB | fits (encoders offloaded) | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | tight | 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
💜 Project    ｜    🖥️ GitHub    |   🤖 MS Space   |   🤖 MS Model   |   🤗 HF Model   |    📑 Paper   
Wan-Dancer: A Hierarchical Framework for Minute-scale Coherent Music-to-Dance Generation
Clone the repo:
git clone https://github.com/Wan-Video/Wan-Dancer.git
cd Wan-Dancer
Install dependencies:
python -m venv venv_wan_dancer
source venv_wan_dancer/bin/activate
# Install package in editable mode
pip install -e .
# Install additional and specific versions dependencies
pip install moviepy loguru librosa
pip install https://mirrors.aliyun.com/pytorch-wheels/cu124/torch-2.6.0+cu124-cp310-cp310-linux_x86_64.whl
pip install torchvision==0.21.0
pip install diffusers==0.34.0
pip install yunchang==0.5.0
pip install flash_attn==2.6.3
pip install xfuser==0.4.0
pip install transformers==4.46.2
| Models | Download Links | Description |
|---|---|---|
| Wan-Dancer-14B | 🤗 Huggingface 🤖 ModelScope | Music-to-Dance |
Download models using huggingface-cli:
pip install "huggingface_hub[cli]"
huggingface-cli download Wan-AI/Wan-Dancer-14B --local-dir ./Wan-Dancer-14B
Download models using modelscope-cli:
pip install modelscope
modelscope download Wan-AI/Wan-Dancer-14B --local_dir ./Wan-Dancer-14B
Wan-Dancer can generate long-duration, high-quality, rhythmic dance videos from music with global structure and temporal continuity. Our method decouples the process into global keyframe planning and local temporal refinement, leveraging full-track musical context to ensure long-range coherence.
Run the global stage script:
cd Wan-Dancer
./gen_video_global.sh
| Parameter | Description |
|---|---|
seed | Random seed for reproducibility. |
image_path | Path to reference image. Example: gen_video/ref_image/1001.jpg |
prompt_path | Path to prompt file (defines dance style).Available styles:Chinese Classic Dance: gen_video/prompt/古典舞_global.txtK-Pop Dance: gen_video/prompt/kpop_global.txtStreet Dance: gen_video/prompt/街舞_global.txtTap Dance: gen_video/prompt/踢踏舞_global.txtLatin Dance: gen_video/prompt/拉丁舞_global.txt |
music_path | Path to input music file. Example: gen_video/music/ChineseClassicDance.WAV |
output_folder | Output directory for generated video. |
timestamp | Timestamp identifier for output files. |
num_inference_steps | Number of diffusion inference steps (e.g., 48). |
Run the local refinement stage:
cd Wan-Dancer
./gen_video_local.sh
| Parameter | Description |
|---|---|
global_video_path | Path to the global video generated in Step 1. Required for local refinement. |
prompt_path | Path to prompt file (defines dance style).Available styles:Chinese Classic Dance: gen_video/prompt/古典舞_local.txtK-Pop Dance: gen_video/prompt/kpop_local.txtStreet Dance: `gen_video/prompt/ |
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. ComfyUI is installed on it. Open ComfyUI through the tunnel and load the workflow from the model's card on Hugging Face; choose this model's file in its loader.
# on your rented machine (the ssh line is on its page in the console)
# get REPO FILE FOLDER: one file into /workspace/models/FOLDER, where ComfyUI loads it from
get() { hf download "$1" "$2" --local-dir /workspace/hf-files && mkdir -p "/workspace/models/$3" && mv "/workspace/hf-files/$2" "/workspace/models/$3/$4"; }
# the model (32.1 GB)
get Wan-AI/Wan-Dancer-14B global_model.safetensors diffusion_models
start-comfyui# on your computer, in a second terminal: ComfyUI in your browser at http://localhost:8188
# HOST and PORT are your machine's, from its page in the console
ssh -L 8188:localhost:8188 dev@HOST -p PORT