SD.Next: Advanced Implementation of Stable Diffusion
 
 
 
 
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README.md

SD.Next

SD.Next: All-in-one WebUI for AI generative image and video creation

Last update License Discord Sponsors

Docs | Wiki | Discord | Changelog


Table of contents

SD.Next Features

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

  • Fully localized: ▹ English | Chinese | Russian | Spanish | German | French | Italian | Portuguese | Japanese | Korean
  • Multiple UIs!
    Standard | Modern
  • Multiple diffusion models!
  • Built-in Control for Text, Image, Batch and Video processing!
  • Multiplatform!
    Windows | Linux | MacOS | nVidia CUDA | AMD ROCm | 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
  • Interrogate/Captioning with 150+ OpenCLiP models and 20+ built-in VLMs
  • Built-in queue management
  • Built in installer with automatic updates and dependency management
  • Mobile compatible

Main interface using StandardUI:
screenshot-standardui

Main interface using ModernUI:

screenshot-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

Plus Docker container receipes for: CUDA, ROCm, Intel IPEX and OpenVINO

Getting started

[!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

Evolution

starts

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