The FLUX.1 suite consists of three variants: FLUX.1 [pro], FLUX.1 [dev], and FLUX.1 [schnell]. FLUX.1 [pro] offers state-of-the-art performance in image generation, with top-of-the-line prompt following, visual quality, image detail, and output diversity. FLUX.1 [dev] is an open-weight, guidance-distilled model for non-commercial applications, offering similar quality and prompt adherence capabilities as FLUX.1 [pro]. FLUX.1 [schnell] is the fastest model, tailored for local development and personal use.
The FLUX.1 models are based on a hybrid architecture of multimodal and parallel diffusion transformer blocks, scaled to 12B parameters. They improve over previous state-of-the-art diffusion models by building on flow matching, a general and conceptually simple method for training generative models. The models also incorporate rotary positional embeddings and parallel attention layers to increase model performance and improve hardware efficiency.
FLUX.1 defines the new state-of-the-art in image synthesis, surpassing popular models like Midjourney v6.0, DALL·E 3 (HD), and SD3-Ultra in various aspects. The models support a diverse range of aspect ratios and resolutions, and are specifically finetuned to preserve the entire output diversity from pretraining.
Key Features:
- Three variants of FLUX.1 models: FLUX.1 [pro], FLUX.1 [dev], and FLUX.1 [schnell]
- State-of-the-art performance in image generation
- Hybrid architecture of multimodal and parallel diffusion transformer blocks
- Scaled to 12B parameters
- Supports diverse range of aspect ratios and resolutions
- Specifically finetuned to preserve entire output diversity from pretraining
- FLUX.1 [pro] available via API, Replicate, and fal.ai, with dedicated and customized enterprise solutions available
- FLUX.1 [dev] available on HuggingFace, with weights available for non-commercial applications
- FLUX.1 [schnell] available under an Apache2.0 license, with weights available on Hugging Face and inference code available on GitHub and in HuggingFace’s Diffusers