FLUX.1 [dev]
12B-parameter rectified-flow transformer for text-to-image, guidance-distilled from the FLUX.1 [pro] teacher. Currently the most-liked model on Hugging Face (~12.9k likes). Sets a new open-weights bar for prompt adherence, typography, and anatomy at 1024px native resolution.
The current open-weights image-gen frontier — nothing else comes close on prompt adherence or typography. Disqualified for anything shipping to paying users by the BFL non-commercial license; pick schnell (Apache-2.0) or pay for the BFL API if revenue is on the line.
Overview
12B-parameter rectified-flow transformer for text-to-image, guidance-distilled from the FLUX.1 [pro] teacher. Currently the most-liked model on Hugging Face (~12.9k likes). Sets a new open-weights bar for prompt adherence, typography, and anatomy at 1024px native resolution.
Strengths
- 12B MMDiT (rectified flow) — state-of-the-art prompt adherence among open weights
- Renders legible in-image text, a long-standing SD weakness
- Strong hands/anatomy compared to SDXL-class models
- Native 1024px, supports up to ~2MP without obvious artifacts
- Mature ecosystem: ComfyUI, diffusers, LoRA training, FP8/NF4/GGUF quantizations
Weaknesses
- Non-commercial license — outputs cannot be used in commercial products without a BFL license
- ~24GB VRAM at BF16; needs FP8/NF4 quantization to fit on 12-16GB consumer cards
- Slow vs SDXL: 20-50 sampling steps at 1024px (~10-30s on RTX 4090)
- Distillation from [pro] caps the ceiling — guidance can be brittle at high CFG
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 6.6 GB | 9 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of FLUX.1 [dev].
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run FLUX.1 [dev]?
Can I use FLUX.1 [dev] commercially?
What's the context length of FLUX.1 [dev]?
Source: huggingface.co/black-forest-labs/FLUX.1-dev
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify FLUX.1 [dev] runs on your specific hardware before committing money.