Image Diffusion implementation with advanced features

Wiki | Discord | Changelog

Table of contents

• 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
• Multiple backends!
  ▹ Diffusers | Original
• Platform specific autodetection and tuning performed on install
• Optimized processing with latest torch developments with built-in support for torch.compile
  and multiple compile backends: Triton, ZLUDA, StableFast, DeepCache, OpenVINO, NNCF, IPEX, OneDiff
• Improved prompt parser
• Built-in queue management
• Enterprise level logging and hardened API
• 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 Wiki

Model support

Additional models will be added as they become available and there is public interest in them
See models overview for details on each model, including their architecture, complexity and other info

• RunwayML Stable Diffusion 1.x and 2.x (all variants)
• StabilityAI Stable Diffusion XL, StabilityAI Stable Diffusion 3.0 Medium, StabilityAI Stable Diffusion 3.5 Medium, Large, Large Turbo
• StabilityAI Stable Video Diffusion Base, XT 1.0, XT 1.1
• StabilityAI Stable Cascade Full and Lite
• Black Forest Labs FLUX.1 Dev, Schnell
• AuraFlow
• AlphaVLLM Lumina-Next-SFT
• Playground AI v1, v2 256, v2 512, v2 1024 and latest v2.5
• Tencent HunyuanDiT
• OmniGen
• Meissonic
• Kwai Kolors
• CogView 3+
• LCM: Latent Consistency Models
• aMUSEd 256 and 512
• Segmind Vega, Segmind SSD-1B, Segmind SegMoE SD and SD-XL, Segmind SD Distilled (all variants)
• Kandinsky 2.1 and 2.2 and latest 3.0
• PixArt-α XL 2 Medium and Large, PixArt-Σ
• Warp Wuerstchen
• Tsinghua UniDiffusion
• DeepFloyd IF Medium and Large
• ModelScope T2V
• BLIP-Diffusion
• KOALA 700M
• VGen
• SDXS
• Hyper-SD

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

Warning

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

Tip

All command line options can also be set via env variable For example --debug is same as set SD_DEBUG=true

Backend support

SD.Next supports two main backends: Diffusers and Original:

• Diffusers: Based on new Huggingface Diffusers implementation
  Supports all models listed below
  This backend is set as default for new installations
• Original: Based on LDM reference implementation and significantly expanded on by A1111
  This backend and is fully compatible with most existing functionality and extensions written for A1111 SDWebUI
  Supports SD 1.x and SD 2.x models
  All other model types such as SD-XL, LCM, Stable Cascade, PixArt, Playground, Segmind, Kandinsky, etc. require backend Diffusers

Collab

• We'd love to have additional maintainers (with comes with full repo rights). If you're interested, ping us!
• In addition to general cross-platform code, desire is to have a lead for each of the main platforms
  This should be fully cross-platform, but we'd really love to have additional contributors and/or maintainers to join and help lead the efforts on different platforms

Credits

• Main credit goes to Automatic1111 WebUI for 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 Wiki 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

Sponsors