Flux image · 12GB VRAM

Best Flux Model for 12GB VRAM (12GB VRAM)

The FP8 sweet spot for Flux.1 on a 12GB GPU

📅 Published: July 7, 2026🔄 Last Updated: July 2026✓ Manually Reviewed

Short answer

The best Flux model for 12GB VRAM in 2026 is Flux.1 dev FP8 — about 11GB in ComfyUI and ~25 seconds per 1024px image on an RTX 4070. 12GB is the sweet spot where Flux stops needing aggressive quantization: FP8 keeps almost all of the FP16 quality. GGUF Q8 is an alternative with slightly lower VRAM. Full FP16 Flux (~24GB) still needs a 24GB card.

Models that fit in 12GB VRAM

Tested reference: RTX 4070 / RTX 3060 12GB. Figures are for a 1024px image.

Model	Size	Build	VRAM used	Speed
WINNERFlux.1 dev FP8 Best quality-per-VRAM on 12GB — visually near-identical to FP16. `ComfyUI FP8 checkpoint`	12B	FP8	~11GB	~25s / image
Flux.1 dev GGUF Q8 A bit more headroom than FP8; use if you want higher resolution. `ComfyUI + GGUF loader`	12B	GGUF Q8	~10GB	~28s / image
Flux.1 Schnell FP8 4-step, Apache-2.0 — very fast drafts at near-FP8 quality. `ComfyUI Schnell FP8`	12B	FP8	~11GB	~6s / image

What won't fit in 12GB

✗Flux.1 dev FP16 (needs ~24GB) — Full precision — needs 24GB.

How to fit more in 12GB

→FP8 is the 12GB sweet spot — you rarely need GGUF quantization at this tier.
→12GB lets you push to 1536px or run a LoRA stack that 8GB cannot.
→Keep the T5 encoder in FP8 too; loading it in FP16 costs ~4GB extra.

Quick start

Get ComfyUI

git clone https://github.com/comfyanonymous/ComfyUI

Load the FP8 checkpoint

Drop flux1-dev-fp8.safetensors into models/checkpoints

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Frequently asked questions

Is 12GB VRAM good for Flux?

Yes — 12GB is the sweet spot. Flux.1 dev FP8 (~11GB) runs at ~25s/image with near-FP16 quality, no aggressive quantization needed, and you can add LoRAs or push resolution.

Flux FP8 vs GGUF Q4 quality?

FP8 (12GB) is clearly better than the GGUF Q4 you’d run on 8GB — sharper detail and better prompt adherence. If you have 12GB, use FP8.

Can 12GB run full FP16 Flux?

No — FP16 Flux needs ~24GB. FP8 on 12GB is visually near-identical for the vast majority of prompts.

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