city96/ComfyUI-GGUF

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3953 stars · 364 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A ComfyUI custom node pack that adds GGUF quantization support for loading diffusion models like FLUX and Stable Diffusion 3.5 in low-bitrate quantized formats. It enables running large transformer-based image models on low-end GPUs with reduced VRAM usage.

Use cases

• run FLUX.1 on a low-VRAM GPU with GGUF quantization
• load quantized Stable Diffusion 3.5 models in ComfyUI
• reduce VRAM usage when generating images with diffusion models
• load a quantized T5 text encoder in ComfyUI
• use GGUF model files with the ComfyUI Unet loader
• generate images with variable bitrate quantized DiT models

When to choose

• you use ComfyUI and want to run large diffusion models on limited GPU memory
• you have pre-quantized GGUF versions of FLUX or SD3.5 models
• you want to quantize the T5 text encoder to save additional VRAM

When to avoid

• you need quantization for conv2d-based UNET models, which is not supported
• you don't use ComfyUI for image generation
• you need fully stable LoRA support, which is still experimental

Facets

plugin · maturity active

llm-inference machine-learning image-processing plugin-system machine-learning image-processing developer-tools python cross-platform comfyui gguf quantization stable-diffusion flux diffusion-models vram-optimization custom-nodes gpu

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markdown · JSON · MCP: product_card(name="city96/ComfyUI-GGUF")