Flux makes the best AI images you can generate at home, and you can run it on a normal GPU — even a 12GB card, thanks to quantized versions. Here's exactly how, and what VRAM you need.
You run it through ComfyUI, the dominant local image-generation tool, with a Flux model file — and the good news is you don't need a monster GPU. Flux.1 Dev, the community's high-quality standard, needs about 10-12GB of VRAM normally, or as little as 6-7GB with a GGUF Q4 quantized version; the faster Flux.1 Schnell runs on 8GB. Flux makes the best AI images you can generate at home in 2026, better than Stable Diffusion, and it's genuinely runnable on a normal graphics card. Here's exactly how, and which variant fits your GPU.
Step 1: install ComfyUI and pick a Flux variant
**ComfyUI** is the tool to use — its node-based workflow is a little more involved than the Forge interface for Stable Diffusion, but it has the best VRAM efficiency and the widest model support, and the ComfyUI-GGUF plugin lets you load quantized models to fit smaller cards. Then pick your Flux flavor. Flux.1 Dev (a 12-billion-parameter model) is the community standard for quality and what most people want. Flux.1 Schnell is a distilled 4B version that's faster and Apache-licensed (commercial-friendly), and it runs on less VRAM. If you have a big card, the newer Flux.2 family pushes quality further. For most people: Flux.1 Dev if you have the VRAM, Schnell or a quantized Dev if you don't.
Flux variants and VRAM needs
Flux.1 Schnell (4B)
Variant
~8GB
VRAM needed
Fast, Apache license
Flux.1 Dev (12B) — GGUF Q4
Variant
~6-7GB
VRAM needed
Quality on a small card
Flux.1 Dev (12B) — full
Variant
10-12GB (24GB ideal)
VRAM needed
The quality standard
Flux.2 Klein 4B / 9B
Variant
12GB / 16GB
VRAM needed
Newer, better
Variant
VRAM needed
Notes
Flux.1 Schnell (4B)
~8GB
Fast, Apache license
Flux.1 Dev (12B) — GGUF Q4
~6-7GB
Quality on a small card
Flux.1 Dev (12B) — full
10-12GB (24GB ideal)
The quality standard
Flux.2 Klein 4B / 9B
12GB / 16GB
Newer, better
Flux.1 Dev is the best local image model — and a GGUF Q4 version runs it on as little as 6-7GB of VRAM. · Unsplash
Step 2: fit it to your VRAM with quantization
The trick that makes Flux runnable on normal cards is quantization. Full Flux.1 Dev in FP16 wants ~24GB, but you rarely need that. FP8 cuts VRAM use nearly in half with quality loss that's usually imperceptible in blind tests — that alone gets Dev onto a 12GB card comfortably. Go further with GGUF quantization (via ComfyUI-GGUF), and a Q4 version of Flux.1 Dev fits in ~6-7GB, meaning even an RTX 3060 12GB or a 8GB card can run high-quality Flux. You can find GGUF versions of Flux.1 Dev, Schnell, and Flux.2 Dev on Civitai and Hugging Face. So the workflow is: pick the quantization that fits your card, load it in ComfyUI, and generate. It's the same quantization idea that runs text LLMs on modest hardware, applied to image models.
Quick answers
How do I run Flux locally?
Install ComfyUI (the standard local image-generation tool), then download a Flux model and load it. Use Flux.1 Dev for the best quality (needs ~10-12GB of VRAM, or ~6-7GB with a GGUF Q4 quantized version) or Flux.1 Schnell for speed on ~8GB. The ComfyUI-GGUF plugin lets you load quantized models to fit smaller cards. Once loaded, type a prompt and generate — it runs free, private, and offline on your own GPU, with no subscription or per-image fees.
What VRAM do I need to run Flux?
It depends on the variant and quantization. Flux.1 Dev (the quality standard) needs about 10-12GB of VRAM normally, 24GB for full FP16 quality, but only ~6-7GB with a GGUF Q4 quant. Flux.1 Schnell, the faster distilled model, runs on ~8GB. FP8 quantization nearly halves VRAM use with minimal quality loss. So even a 8-12GB card like the RTX 3060 12GB can run high-quality Flux using quantized versions — you don't need a 24GB GPU.
Is Flux better than Stable Diffusion for local image generation?
For image quality, Flux is generally considered the best local model in 2026, surpassing Stable Diffusion (including SDXL) in prompt adherence and detail. Flux.1 Dev is the community favorite for high-quality generation. Stable Diffusion still has advantages in ecosystem maturity, model variety, and lower VRAM requirements for its smaller models. But if you want the best-looking AI images you can generate at home and have a capable GPU (or use a quantized Flux version), Flux is the top choice.
