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Glossary · Models & Files

What Is a Quantized Model in ComfyUI?

By Earngenix Team ·

⚡ Quick Answer

A quantized model stores its weights using fewer bits of precision than it was originally trained with. This shrinks the file size and the VRAM needed to run it, at some cost to output quality. GGUF and fp8 are the two quantization formats you'll run into most often in ComfyUI.

Quantization is the general idea; GGUF and fp8 are two specific, different ways of putting that idea into practice.

Where You'll See It

Model download pages label a smaller release as "quantized," or name its specific level directly — "Q4," "Q8," or "fp8" — next to the full-precision original, usually released as bf16 or fp16.

Quick Example

A checkpoint's full bf16 release might be around 24 GB, while its quantized fp8 or GGUF release comes in closer to 8–12 GB — letting it run on a much smaller graphics card.

Quantization compresses an existing, already-trained model. It's a different process from distillation, which trains a new, smaller model from scratch to imitate a bigger one — the two techniques can even be combined.

Frequently Asked Questions

It usually causes some quality loss, but for transformer-style models the difference at moderate quantization levels (like fp8 or Q6/Q8 GGUF) is often hard to notice without close comparison. Heavier quantization shows more visible degradation.

Neither is universally "better" — fp8 is a single fixed precision level that’s simple to use, while GGUF offers several selectable quant levels, giving more control over the size-versus-quality trade-off at the cost of a slightly more involved setup.

Yes, tools exist to convert a full-precision checkpoint into GGUF or fp8 yourself, though most people simply download a pre-quantized version that a model’s community has already published.

See It In Action

Not sure which version to download?

Our VRAM & Hardware Guide matches models to what your GPU can actually run.

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

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