Imagem
stable-diffusion.cpp
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++
★ 7,5 mil estrelasMIT
Ver o guia →flux é um projeto de imagem de código aberto de black-forest-labs (black-forest-labs/flux no GitHub). Tem 26.009 estrelas no GitHub e 1.925 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 31 de julho de 2025.
Black Forest Labs' official inference repo for the FLUX.1 image generation models
Decide what you want to achieve with flux and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
The reference implementation from the model's creators for running FLUX.1 locally.
Covers the open-weight FLUX.1 variants with their individual licenses explained in the repo.
Includes examples for Kontext, the image editing/context model, including usage-tracking notes.
A documented TensorRT installation path for NVIDIA performance setups.
Explains when and how to use the hosted FLUX API instead of local weights.
A dedicated section explains licensing the models for commercial use.
Get the official FLUX inference code.
git clone https://github.com/black-forest-labs/flux.git
cd fluxUse Python 3.10 and install the package with all extras, exactly as the README documents.
python3.10 -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"Download an open-weight model's weights as directed and run the README's example inference for that model.
# see the README's model sections for the exact example command per modelflux is maintained by the black-forest-labs organization/account on GitHub, together with open-source contributors, in the public repository black-forest-labs/flux.
Yes — the code is open source under the Apache-2.0 license. You can use, modify and redistribute it under that license's terms.
Local open-weight models need no API key (weights download from Hugging Face under each model's license); the hosted API and some models require an account and commercial licensing.
SDXL has a larger community ecosystem; FLUX.1 is chosen for its prompt fidelity and quality, with this repo as the vendor's reference implementation.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++
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