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flux

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Official inference repo for FLUX.1 models

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Official inference repo for FLUX.1 models

FLUX

by Black Forest Labs: https://bfl.ai.

Documentation for our API can be found here: docs.bfl.ai.

This repo contains minimal inference code to run image generation & editing with our Flux open-weight models.

Local installation

cd $HOME && git clone https://github.com/black-forest-labs/flux
cd $HOME/flux
python3.10 -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"

Local installation with TensorRT support

If you would like to install the repository with TensorRT support, you currently need to install a PyTorch image from NVIDIA instead. First install enroot, next follow the steps below:

cd $HOME && git clone https://github.com/black-forest-labs/flux
enroot import 'docker://[email protected]#nvidia/pytorch:25.01-py3'
enroot create -n pti2501 nvidia+pytorch+25.01-py3.sqsh
enroot start --rw -m ${PWD}/flux:/workspace/flux -r pti2501
cd flux
pip install -e ".[tensorrt]" --extra-index-url https://pypi.nvidia.com

Open-weight models

We are offering an extensive suite of open-weight models. For more information about the individual models, please refer to the link under Usage.

Name Usage HuggingFace repo License FLUX.1 [schnell] Text to Image https://huggingface.co/black-forest-labs/FLUX.1-schnell apache-2.0 FLUX.1 [dev] Text to Image https://huggingface.co/black-forest-labs/FLUX.1-dev FLUX.1-dev Non-Commercial License FLUX.1 Fill [dev] In/Out-painting https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev FLUX.1-dev Non-Commercial License FLUX.1 Canny [dev] Structural Conditioning https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev FLUX.1-dev Non-Commercial License FLUX.1 Depth [dev] Structural Conditioning https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev FLUX.1-dev Non-Commercial License FLUX.1 Canny [dev] LoRA Structural Conditioning https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev-lora FLUX.1-dev Non-Commercial License FLUX.1 Depth [dev] LoRA Structural Conditioning https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev-lora FLUX.1-dev Non-Commercial License FLUX.1 Redux [dev] Image variation https://huggingface.co/black-forest-labs/FLUX.1-Redux-dev FLUX.1-dev Non-Commercial License FLUX.1 Kontext [dev] Image editing https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev FLUX.1-dev Non-Commercial License FLUX.1 Krea [dev] Text to Image https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev FLUX.1-dev Non-Commercial License

The weights of the autoencoder are also released under apache-2.0 and can be found in the HuggingFace repos above.

API usage

Our API offers access to all models including our Pro tier non-open weight models. Check out our API documentation docs.bfl.ai to learn more.

Licensing models for commercial use

You can license our models for commercial use here: https://bfl.ai/pricing/licensing

As the fee is based on a monthly usage, we provide code to automatically track your usage via the BFL API. To enable usage tracking please select track_usage in the cli or click the corresponding checkmark in our provided demos.

Example: Using FLUX.1 Kontext with usage tracking

We provide a reference implementation for running FLUX.1 with usage tracking enabled for commercial licensing. This can be customized as needed as long as the usage reporting is accurate.

For the reporting logic to work you will need to set your API key as an environment variable before running:

export BFL_API_KEY="your_api_key_here"

You can call FLUX.1 Kontext [dev] like this with tracking activated:

python -m flux kontext --track_usage --loop

For a single generation:

python -m flux kontext --track_usage --prompt "replace the logo with the text 'Black Forest Labs'"

The above reporting logic works similarly for FLUX.1 [dev] and FLUX.1 Tools [dev].

Note that this is only required when using one or more of our open weights models commercially. More information on the commercial licensing can be found at the BFL Helpdesk.

Citation

If you find the provided code or models useful for your research, consider citing them as:

…

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发布日期2026年8月1日
最后更新2026年9月9日
分类编程语言
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