Flux 2

Flux 2

Open-weight rectified flow Transformer for image generation and editing.

5.0
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Flux 2 screenshot

Overview

FLUX 2 Dev (FLUX.2-dev) is a frontier-level, open-weight rectified flow Transformer for image generation and editing, developed by Black Forest Labs. It integrates a 32B rectified flow core, a long-context vision–language model (VLM), and multi-reference editing capabilities to produce production-grade visuals. It is designed for various applications including high-fidelity animal renders, ad creatives, hero banners, 3D concept art, product renders, interactive filters, and avatars.

How to Use

FLUX 2 Dev can be utilized through several platforms: Hugging Face Diffusers (Python), Cloudflare Workers AI, and ComfyUI. For Hugging Face, users can import `Flux2Pipeline` to perform text-to-image generation, specifying prompts, inference steps (12-20 for drafts, 28-40 for production), and guidance scale (3-5). For Cloudflare Workers AI, deployment involves using the `env.AI.run` API with the `@cf/black-forest-labs/flux-2-dev` model for edge inference. ComfyUI integration requires updating the software, downloading `.safetensors` checkpoints, and loading pre-made templates, which can be extended with control nodes or LoRA adapters.

Core Features

Multi-reference editing to maintain character, style, and branding consistency across images. High-resolution output, generating up to 4MP / 4K-class images with improved text rendering, lighting, hands, and faces. Efficient inference achieved through rectified flow sampling and guidance distillation, reducing steps and guidance scale for faster iterations. Long-context Vision–Language Model (VLM) with approximately 32K tokens to process detailed prompts, layouts, and hex color instructions. Flexible deployment options supporting Hugging Face Diffusers, Cloudflare Workers AI, NVIDIA RTX FP8/FP4 pipelines, and ComfyUI templates. Ecosystem readiness with Diffusers integration, quantized variants, control hints, and extension APIs.

Use Cases

  1. 1 Product marketing: Creating brand-consistent ad creatives, hero banners, and multi-language posters.
  2. 2 Creative pipelines: Generating concept art, storyboards, character sheets, and animation keyframes with multi-reference consistency.
  3. 3 Interactive experiences: Developing edge-hosted filters, avatars, and social thumbnails via Workers AI or custom RTX endpoints.
  4. 4 Ad creatives, hero banners, 3D concept art, product renders, interactive filters, avatars, rapid prototyping.

Frequently Asked Questions

What is FLUX 2 Dev?
FLUX 2 Dev is an open-weight rectified flow Transformer model for image generation and editing. It is the developer-focused release of the FLUX 2 model family.
How is FLUX 2 different from FLUX.1?
FLUX 2 introduces a rectified flow Transformer architecture with stronger generation and editing capabilities. It offers better performance, wider resolution support, and new features like multi-reference inputs.
How many steps should I use?
You can use as few as 4-8 steps for faster results, and more steps for higher quality. The recommended step counts are listed in the model documentation and examples.
Does FLUX 2 Dev support multi-reference?
Yes, FLUX 2 Dev supports multi-reference inputs. This allows you to use multiple reference images to guide generation.
Can I run FLUX 2 Dev on a single GPU?
Yes, FLUX 2 Dev is designed to run on a single GPU. Hardware requirements depend on resolution and batch size, so check the repository for specifics.
How to deploy FLUX 2 Dev at the edge?
You can deploy FLUX 2 Dev at the edge using optimized runtimes such as ONNX or TensorRT, with providers like Cloudflare Workers AI. Refer to the deployment guides in the repository.
What resolutions does FLUX 2 Dev support?
FLUX 2 Dev supports a range of resolutions, including higher resolutions with multiple aspect ratios. See the documentation for the full supported resolution list.
How good is FLUX 2 Dev at text rendering?
FLUX 2 Dev has significantly improved text rendering compared to earlier versions. It handles longer and more complex text prompts accurately.
What are best practices for prompting FLUX 2 Dev?
Use clear, descriptive prompts and specify the style, composition, and text you want. Refer to the prompt guides and examples in the model card for the best results.
Where can I find FLUX 2 Dev resources?
Resources are available in the official FLUX GitHub repository and model card. Community guides and Hugging Face pages are also good places to start.