Model reference · open weights
Wan2.1-T2V is an open-weight video model from city96. Wan2.1-T2V-14B-gguf (GGUF) weighs 10.1 GB; the smallest configuration that runs it is RTX 3060 12 GB.
Summary of the city96/Wan2.1-T2V-14B-gguf model card, 2026-10-01
What it is
| Released by | city96 |
|---|---|
| Released | 2025-02-26 |
| VRAM | 10.1 GB for the weights |
What it runs on
| Card | Weights | Memory |
|---|---|---|
| RTX 3060 12 GB | tight | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 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 a direct GGUF conversion of Wan-AI/Wan2.1-T2V-14B
All quants are created from the FP32 base file, though I only uploaded FP16 due to it exceeding the 50GB max file limit and gguf-split loading not currently being supported in ComfyUI-GGUF.
The model files can be used with the ComfyUI-GGUF custom node.
Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions.
The VAE can be downloaded from this repository by Kijai
Please refer to this chart for a basic overview of quantization types.
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
How it works
Running it yourself
Rent a machine by the hour. ComfyUI is installed on it. Open ComfyUI through the tunnel, then Templates → Wan 2.1 Text to Video. Its model loader takes .safetensors files: replace it with Unet Loader (GGUF) and choose this model's file there.
# on your rented machine (the ssh line is on its page in the console)
# the GGUF loader nodes, once per machine
git clone https://github.com/city96/ComfyUI-GGUF /opt/ComfyUI/custom_nodes/ComfyUI-GGUF
pip install -r /opt/ComfyUI/custom_nodes/ComfyUI-GGUF/requirements.txt
# 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 (9.4 GB)
get city96/Wan2.1-T2V-14B-gguf wan2.1-t2v-14b-Q4_K_M.gguf unet
# what the template also loads “Wan 2.1 Text to Video” (6.5 GB)
get Comfy-Org/Wan_2.1_ComfyUI_repackaged split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors text_encoders
get Comfy-Org/Wan_2.1_ComfyUI_repackaged split_files/vae/wan_2.1_vae.safetensors vae
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