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black-forest-labs/flux2

FLUX.2 [klein] squeezes sub-second image generation onto consumer GPUs

Official inference code for Black Forest Labs' FLUX.2 open-weight models, spanning a sub-second 4B-parameter family to a 32B-parameter flagship for local image generation and editing.

flux2
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What it does

The repository hosts minimal inference scripts for Black Forest Labs’ FLUX.2 suite. It covers the lightweight FLUX.2 [klein] family—distilled 4B and 9B transformers that generate and edit images in under a second on modern consumer GPUs—and the 32B-parameter FLUX.2 [dev] model for higher-fidelity output. All variants handle text-to-image, single-reference editing, and multi-reference editing through a unified architecture.

The interesting bit

The real maneuver is the licensing and sizing split. The 4B klein model ships under Apache 2.0 and fits inside roughly 8 GB of VRAM, making it a rare fully open-weight, commercially permissive option that competes on latency. Meanwhile, the 32B dev model is gated behind a non-commercial license and essentially requires data-center hardware unless you adopt Hugging Face quantization workarounds.

Key highlights

  • FLUX.2 [klein] 4B runs in sub-second inference on hardware like an RTX 3090 or 4070 (~8 GB VRAM).
  • All klein and dev models support unified text-to-image, single-reference, and multi-reference editing in one checkpoint.
  • The 4B klein models are Apache 2.0; 9B klein, klein Base, and dev use a non-commercial license.
  • FLUX.2 [dev] offers prompt upsampling via a local 24B Mistral model or an external OpenRouter API call.
  • Built-in optional invisible watermarking and C2PA metadata recommendations for output provenance.

Caveats

  • FLUX.2 [dev] requires H100-equivalent VRAM for its standard inference script; consumer GPU support depends on external Hugging Face quantization, not code in this repo.
  • The 9B and dev weights are non-commercial, so the Apache 2.0 promise only applies to the 4B variants.
  • The repository is explicitly “minimal inference code,” so expect plumbing rather than a polished application framework.

Verdict

Ideal for researchers and integrators who want open weights to hack on, especially the 4B klein model for real-time or edge prototypes. Pass if you need a turnkey commercial product or a unified UI, because this is strictly the engine block.

Frequently asked

What is black-forest-labs/flux2?
Official inference code for Black Forest Labs' FLUX.2 open-weight models, spanning a sub-second 4B-parameter family to a 32B-parameter flagship for local image generation and editing.
Is flux2 open source?
Yes — black-forest-labs/flux2 is open source, released under the Apache-2.0 license.
What language is flux2 written in?
black-forest-labs/flux2 is primarily written in Python.
How popular is flux2?
black-forest-labs/flux2 has 2.5k stars on GitHub.
Where can I find flux2?
black-forest-labs/flux2 is on GitHub at https://github.com/black-forest-labs/flux2.

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