Wan 2.1 I2V 14B 720P GGUF

The other files required can be downloaded from this repository by Comfy-Org

Please refer to this chart for a basic overview of quantization types.

wan2.1-i2v-14b-720p-Q3_K_M.gguf

gguf · 8.00 GB · SHA-256 3a430a457515…889b · Hugging Face

--- base_model: Wan-AI/Wan2.1-I2V-14B-720P library_name: gguf quantized_by: city96 tags: - video - video-generation license: apache-2.0 pipeline_tag: image-to-video language: - en - zh --- This is a direct GGUF conversion of [Wan-AI/Wan2.1-I2V-14B-720P](https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-720P) 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](https://github.com/city96/ComfyUI-GGUF) custom node. Place model files in `ComfyUI/models/unet` - see the GitHub readme for further install instructions. The other files required can be downloaded from [this repository by Comfy-Org](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files) Please refer to [this chart](https://github.com/ggerganov/llama.cpp/blob/master/examples/perplexity/README.md#llama-3-8b-scoreboard) for a basic overview of quantization types.