Black Forest Labs releases FLUX 3 Image Klein with 8 GB VRAM support
Black Forest Labs' open-weights image model FLUX 3 Image Klein runs on consumer GPUs with just 8 GB of VRAM
- Who
- Black Forest Labs
- What
- released FLUX 3 Image Klein, a 5.6-billion-parameter open-weights image generation model
- When
- Quote
Oct 15, 2026 Black Forest Labs has released FLUX 3 Image Klein, a 5.6-billion-parameter open-weights model for text-to-image generation, image editing, and generation with up to ten reference images.
What happened
Black Forest Labs has released FLUX 3 Image Klein, a 5.6-billion-parameter open-weights model for text-to-image generation, image editing, and generation with up to ten reference images. It supports native 4K output, and its INT8 build runs on NVIDIA GPUs with 8 GB of VRAM, generating an image in under 9 seconds on an RTX 4070. The FLUX Kommunity License allows free commercial use for companies making under $5 million annually.
Why it matters
The hardware requirements and commercial license threshold provide concrete context for assessing whether local image generation fits a team's available GPUs and business size.
Reported by 2 sources
The story so far
Black Forest Labs has released FLUX 3 Image Klein, a 5.6-billion-parameter open-weights model for image generation and editing, with launch-day support in Hugging Face Diffusers and vLLM-Omni. The Decoder reported that the model supports up to ten reference images and native 4K output, while its INT8 build runs on NVIDIA GPUs with 8 GB of VRAM and generates an image in under 9 seconds on an RTX 4070. The weights use the FLUX Kommunity License, which permits free commercial use for companies making under $5 million annually. Diffusers supports text-to-image generation, multi-reference image-to-image generation and bounding-box layout control. Its available checkpoints include a distilled model using 16 steps without classifier-free guidance and a base model using 50 steps with it. Hugging Face reported that the distilled model generated a 1024 × 1024 image in 1.93 seconds on an H100 in its benchmark, and provides quantized loading examples and LoRA training scripts. The vLLM team said it worked with Black Forest Labs and NVIDIA to add vLLM-Omni support, including BF16, FP8 and NVFP4 checkpoints. NVIDIA said the model was trained on its GB200 NVL72 hardware and can run on an RTX GPU.
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