FLUX.2-klein-base-4B

The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, **delivering state-of-the-art quality with end-to-end inference in as low as under a second**. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B Base is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. It's a full-capacity foundation model. Undistilled, preserving complete training signal for maximum flexibility. Ideal for fine-tuning, LoRA training, research, and custom pipelines where control matters more than speed. Higher output diversity than the distilled models. For more information, please read our blog post. **Key Features** 1. Exceptional speed and quality-to-size ratio. 2. Ideal for local deployment and fine-tuning on limited hardware. 3. Trained without step or guidance distillation, making FLUX.2 [klein] 4B Base more efficient and flexible. 4. Open weights for customization and fine-tuning to drive science, research, and empower artists to iterate with speed. 5. Outputs can be used for commercial purposes, as described in the Apache 2.0 license. **Usage** We provide a reference implementation of FLUX.2 [klein] 4B Base, as well as sampling code, in a dedicated GitHub repository. Developers and creatives looking to build on top of FLUX.2 [klein] 4B Base are encouraged to use this as a starting point. FLUX.2 [klein] 4B Base is also available in both ComfyUI and Diffusers. **Using with Diffusers 🧨** To use FLUX.2 [klein] 4B Base with the 🧨 Diffusers python library, first install or upgrade diffusers: Then you can use Flux2KleinPipeline to run the model: Limitations This model is not intended or able to provide factual information. While the model can output text, text rendered may be inaccur