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.

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
kleinanddevmodels support unified text-to-image, single-reference, and multi-reference editing in one checkpoint. - The 4B
kleinmodels are Apache 2.0; 9Bklein,kleinBase, anddevuse 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
devweights 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.