README.md

metadata

license: apache-2.0
tags:
  - gguf
  - wan2.2
  - i2v
  - t2v
  - video-generation
  - wan-ai
  - comfyui
  - fp16
language:
  - en
library_name: comfyui
pipeline_tag: image-to-video
base_model:
  - Wan-AI/Wan2.2-I2V-A14B
  - Wan-AI/Wan2.2-T2V-A14B

Model Files

• wan2.2_i2v_high_noise_14B_fp16.gguf: High-noise model in FP16 format (not quantized)
• wan2.2_i2v_low_noise_14B_fp16.gguf: Low-noise model in FP16 format (not quantized)
• wan2.2_t2v_high_noise_14B_fp16.gguf: High-noise model in FP16 format (not quantized)
• wan2.2_t2v_low_noise_14B_fp16.gguf: High-noise model in FP16 format (not quantized)

Format Details

• Important: These are NOT quantized models but FP16 precision models in GGUF container format
• Base model: Wan-AI/Wan2.2-I2V-A14B -Base model: Wan-AI/Wan2.2-T2V-A14B
• Format: GGUF container with FP16 precision (unquantized)
• Original model size: ~27B parameters (14B active per step)
• File sizes:
  • high: 28.6 GB for FP16 (SHA256: 3a7d4e...)
  • low: 28.6 GB (SHA256: 1b4e28...)

Why FP16 in GGUF?

While GGUF is typically used for quantized models, ComfyUI-GGUF extension supports:

• Loading FP16 models in GGUF container format
• This provides compatibility with ComfyUI workflow