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Accelerate your Stable Diffusion inference with the library's universal C/C++ framework design, powered by ONNXRuntime & across platforms.
| Date | Stars |
|---|---|
| 2026-07-24 | 446 |
| 2026-07-25 | 446 |
| 2026-07-28 | 446 |
| 2026-07-30 | 446 |
| 2026-07-31 | 446 |
| 2026-08-06 | 446 |
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<h1 align="center">Agile Diffusers Inference (ADI) </h1>
<p align="center">
<a href="https://opensource.org"><img src="https://img.shields.io/badge/Open_Source-❤️-FDA599?"/></a>
<a href="/LICENSE"><img src="https://img.shields.io/badge/License-GNU_GPLv3-F4E28D"/></a>
<a href="https://onnxruntime.ai"><img src="https://img.shields.io/badge/Powered%20by-ONNXRuntime-blue"/></a>
<a href="https://github.com/Windsander/ADI-Stable-Diffusion/actions">
<img src="https://img.shields.io/github/actions/workflow/status/Windsander/ADI-Stable-Diffusion/test-native.yml?label=All%20platforms" alt="CI Status"/>
</a>
</p>
<br>
**Agile Diffusers Inference (ADI)** is a **C++ library** with **CLI tool**. Purpose to leverage the acceleration capabilities of [ONNXRuntime](https://onnxruntime.ai) and the high compatibility of the .onnx model format to provide a convenient solution for the engineering deployment of Stable Diffusion, with suitable package size & high performance.
## Why choose ONNXRuntime as our Inference Engine?
- **Open Source:** ONNXRuntime is an open-source project, allowing users to freely use and modify it to suit different application scenarios.
- **Scalability:** It supports custom operators and optimizations, allowing for extensions and optimizations based on specific needs.
- **High Performance:** ONNXRuntime is highly optimized to provide fast inference speeds, suitable for real-time applications.
- **Strong Compatibility:** It supports model conversion from multiple deep learning frameworks (such as PyTorch, TensorFlow), making integration and deployment convenient.
- **Cross-Platform Support:** ONNXRuntime supports multiple hardware platforms, including CPU, GPU, TPU, etc., enabling efficient execution on various devices.
- **Community and Enterprise Support:** Developed and maintained by Microsoft, it has an active community and enterprise support, providing continuous updates and maintenance.
## How to install (CLI)?
### Method 1: Install the Command Line Tool Using a Package Manager
```bash
## macOS (Homebrew):
brew tap windsander/adi-stable-diffusion
brew install adi
## Windows (git-Bash + Chocolatey):
curl -L -o adi.1.0.1.nupkg "https://raw.githubusercontent.com/Windsander/ADI-Stable-Diffusion/deploy/adi.1.0.1.nupkg"
choco install adi.1.0.1.nupkg -y
```
### Method 2: Download from the Released Version
You can find the latest available version from the **[Release Assets](https://github.com/Windsander/ADI-Stable-Diffusion/releases)**. The file tree of the package will look like this:
```
--bin
--adi
--lib
--[Corresponding platform's ADI library, e.g., libadi.a]
--[Corresponding platform's ORT library, e.g., libonnxruntime.dylib]
--include
--adi.h
--CHANGELOG.md
--README.md
--LICENSE
```
After unzipping, you can simply install the `bin` and `lib` directories to your system, or just go into the unzipped `bin` directory, and start using `adi`.
### Method 3: Build [adi-lib & adi-cli] Locally
- **An automated script is provided to compile ADI on your device more easily.**
Simply execute the script [auto_build.sh](auto_build.sh):
```bash
# if you do not pass the BUILD_TYPE parameter, the script will use the default Debug build type.
# and, if you not enable certain ORTProvider by [options]], script will choose default ORTProvider by platform
bash ./auto_build.sh
# Example-MacOS:
bash ./auto_build.sh --platform macos --build-type debug
# Example-Windows:
bash ./auto_build.sh --platform windows --build-type debug
# Example-Linux(Ubuntu):
bash ./auto_build.sh --platform linux --build-type debug
# Example-Android:
bash ./auto_build.sh --platform android \
--build-type debug \
--android-ndk /Volumes/AL-Data-W04/WorkingEnv/Android/sdk/ndk/26.1.10909125 \
--android-ver 27
# Example(with Extra Options) as below, build release with CUDA=ON TensorRT=ON, and custom compiler configs
bash ./auto_builExcerpt of 11,170 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e69e4a20e33f7adf, topic:stable-diffusion, name:stable diffusion, desc:stable diffusion