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Glossary · Models & Files

What Is GGUF in ComfyUI?

By Earngenix Team ·

⚡ Quick Answer

GGUF is a compressed model file format, borrowed from the llama.cpp project, that stores an AI model's weights at a lower precision than the original release. This lets big checkpoints run in far less VRAM, at a small, adjustable cost to output quality.

Unlike a single fixed compression level, GGUF ships in several selectable "quant" levels — Q4, Q5, Q8, and more — so you can pick the balance of size versus quality that fits your GPU.

Where You'll See It

GGUF files use the .gguf extension and need the ComfyUI-GGUF custom node pack, which adds a dedicated UNet Loader (GGUF) node in place of the standard checkpoint loader.

Quick Example

A FLUX.1-dev checkpoint that needs roughly 24 GB of VRAM in its original format can run at Q4 GGUF quantization on an 8 GB card, trading some fine detail for the ability to run at all.

GGUF quantization works especially well on transformer/DiT-style models like Flux. Older convolutional UNet architectures tolerate this kind of compression less gracefully.

Frequently Asked Questions

Higher numbers (like Q8) stay closer to the original model’s quality but need more VRAM; lower numbers (like Q4) save more VRAM at a bigger quality cost. Q5 or Q6 is a common middle ground when you have some headroom to spare.

Generally yes, using the standard LoRA loader nodes, though support can vary by custom node version. Check the GGUF loader’s documentation if a LoRA doesn’t seem to apply correctly.

It can be slightly slower per step on some setups because of the extra work needed to unpack the compressed weights, but this is usually a worthwhile trade for being able to run a model that wouldn’t fit in VRAM at all otherwise.

See It In Action

Not sure what your GPU can run?

Our VRAM & Hardware Guide breaks down GGUF, fp8, and full-precision options.

Published: 2026-09-17 · Last updated: 2026-09-17

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