FLUX.1
State-of-the-art open image generation model by Black Forest Labs with rectified flow transformers.
About
FLUX.1 is the image generation model family from Black Forest Labs, a company founded by former Stability AI researchers. The models use a rectified flow transformer architecture and come in two open-weight text-to-image variants: schnell, a fast few-step model released under Apache 2.0, and dev, a guidance-distilled model under a non-commercial license. Specialized editions extend the base capability to inpainting and outpainting (Fill), structural conditioning from Canny edges or depth maps, image variation (Redux), and instruction-based editing (Kontext), with LoRA versions of the conditioning models available. The official repository ships minimal PyTorch inference code requiring Python 3.10 or newer, with optional TensorRT acceleration, and the same models are served through a documented REST API. Running locally typically calls for a GPU with 12 GB or more of VRAM. Developers, artists, and researchers use FLUX.1 both directly and through front ends such as ComfyUI and Diffusers.
Should you use FLUX.1?
Pick it when
Pick FLUX.1 when you want a strong open text-to-image model on a 12 GB GPU with a broad family around it: schnell for fast Apache-2.0 output, plus Fill, Canny, depth, Redux, and Kontext editions for inpainting, control, and editing.
Look elsewhere when
Skip it if you must deploy the dev model commercially, since its license requires a paid BFL license; Chroma or Qwen-Image are Apache-2.0. Under 12 GB, SDXL-based models are the practical choice, and FLUX.2 supersedes it for multi-reference editing.
Alternatives to FLUX.1
- FLUX.2
Successor with 4MP output, better typography, and editing from up to 10 reference images, but the 32B dev checkpoint is far heavier to run.
- Chroma
Rebuilt from schnell under Apache-2.0 with broader styles, avoiding dev's non-commercial license, but positioned as a fine-tuning base.
- Stable Diffusion 3.5
Medium at 2.5B suits smaller GPUs and the license covers smaller businesses, but it has fewer companion editions for fill, variation, and editing.
- Qwen-Image
Apache-2.0 at 20B and built for paragraph-level text rendering with an edit line, but heavier, relying on FP8 or GGUF quantizations for consumer cards.
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Details
- Category
- Image Generation
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- Apache-2.0
- Minimum VRAM
- 12 GB
- Added
- Apr 3, 2026
Tags
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