Image Diffusion implementation with advanced features

Docs | Wiki | Discord | Changelog

Table of contents

• Documentation
• SD.Next Features
• Model support
• Platform support
• Getting started

SD.Next Features

All individual features are not listed here, instead check ChangeLog for full list of changes

• Multiple UIs!
  ▹ Standard | Modern
• Multiple diffusion models!
• Built-in Control for Text, Image, Batch and video processing!
• Multiplatform!
  ▹ Windows | Linux | MacOS | nVidia | AMD | IntelArc/IPEX | DirectML | OpenVINO | ONNX+Olive | ZLUDA
• Platform specific autodetection and tuning performed on install
• Optimized processing with latest torch developments with built-in support for model compile, quantize and compress
  Compile backends: Triton | StableFast | DeepCache | OneDiff | TeaCache | etc.
  Quantization and compression methods: BitsAndBytes | TorchAO | Optimum-Quanto | NNCF
• Built-in queue management
• Built in installer with automatic updates and dependency management
• Mobile compatible

Main interface using StandardUI:

Main interface using ModernUI:

For screenshots and informations on other available themes, see Themes

Model support

SD.Next supports broad range of models: supported models and model specs

Platform support

• nVidia GPUs using CUDA libraries on both Windows and Linux
• AMD GPUs using ROCm libraries on Linux
  Support will be extended to Windows once AMD releases ROCm for Windows
• Intel Arc GPUs using OneAPI with IPEX XPU libraries on both Windows and Linux
• Any GPU compatible with DirectX on Windows using DirectML libraries
  This includes support for AMD GPUs that are not supported by native ROCm libraries
• Any GPU or device compatible with OpenVINO libraries on both Windows and Linux
• Apple M1/M2 on OSX using built-in support in Torch with MPS optimizations
• ONNX/Olive
• AMD GPUs on Windows using ZLUDA libraries

Getting started

• Get started with SD.Next by following the installation instructions
• For more details, check out advanced installation guide
• List and explanation of command line arguments
• Install walkthrough video

Tip

And for platform specific information, check out
WSL | Intel Arc | DirectML | OpenVINO | ONNX & Olive | ZLUDA | AMD ROCm | MacOS | nVidia | Docker

Warning

If you run into issues, check out troubleshooting and debugging guides

Contributing

Please see Contributing for details on how to contribute to this project
And for any question, reach out on Discord or open an issue or discussion

Credits

• Main credit goes to Automatic1111 WebUI for the original codebase
• Additional credits are listed in Credits
• Licenses for modules are listed in Licenses

Evolution

• OSS Stats

Docs

If you're unsure how to use a feature, best place to start is Docs and if its not there,
check ChangeLog for when feature was first introduced as it will always have a short note on how to use it