select text and press Ctrl+Up or Ctrl+Down (or Command+Up or Command+Down if you're on a MacOS) to automatically adjust attention to selected text (code contributed by anonymous user)

Loopback, run img2img processing multiple times

X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters

Textual Inversion

have as many embeddings as you want and use any names you like for them

use multiple embeddings with different numbers of vectors per token

works with half precision floating point numbers

train embeddings on 8GB (also reports of 6GB working)

Extras tab with:

GFPGAN, neural network that fixes faces

CodeFormer, face restoration tool as an alternative to GFPGAN

RealESRGAN, neural network upscaler

ESRGAN, neural network upscaler with a lot of third party models

SwinIR and Swin2SR (see here), neural network upscalers

LDSR, Latent diffusion super resolution upscaling

Resizing aspect ratio options

Sampling method selection

Adjust sampler eta values (noise multiplier)

More advanced noise setting options

Interrupt processing at any time

4GB video card support (also reports of 2GB working)

Correct seeds for batches

Live prompt token length validation

Generation parameters

parameters you used to generate images are saved with that image

in PNG chunks for PNG, in EXIF for JPEG

can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI

can be disabled in settings

drag and drop an image/text-parameters to promptbox

Read Generation Parameters Button, loads parameters in promptbox to UI

Settings page

Running arbitrary python code from UI (must run with --allow-code to enable)

Mouseover hints for most UI elements

Possible to change defaults/mix/max/step values for UI elements via text config

Tiling support, a checkbox to create images that can be tiled like textures

Progress bar and live image generation preview

Can use a separate neural network to produce previews with almost none VRAM or compute requirement

Negative prompt, an extra text field that allows you to list what you don't want to see in generated image

Styles, a way to save part of prompt and easily apply them via dropdown later

Variations, a way to generate same image but with tiny differences

Seed resizing, a way to generate same image but at slightly different resolution

CLIP interrogator, a button that tries to guess prompt from an image

Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway

Batch Processing, process a group of files using img2img

Img2img Alternative, reverse Euler method of cross attention control

Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions

Reloading checkpoints on the fly

Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one

Custom scripts with many extensions from community

Composable-Diffusion, a way to use multiple prompts at once

separate prompts using uppercase AND

also supports weights for prompts: a cat :1.2 AND a dog AND a penguin :2.2

No token limit for prompts (original stable diffusion lets you use up to 75 tokens)

DeepDanbooru integration, creates danbooru style tags for anime prompts

xformers, major speed increase for select cards: (add --xformers to commandline args)

via extension: History tab: view, direct and delete images conveniently within the UI

Generate forever option

Training tab

hypernetworks and embeddings options

Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)

Clip skip

Hypernetworks

Loras (same as Hypernetworks but more pretty)

A separate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt

Can select to load a different VAE from settings screen

Estimated completion time in progress bar

API

Support for dedicated inpainting model by RunwayML

via extension: Aesthetic Gradients, a way to generate images with a specific aesthetic by using clip images embeds (implementation of https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)

Stable Diffusion 2.0 support - see wiki for instructions

Alt-Diffusion support - see wiki for instructions

Now without any bad letters!

Load checkpoints in safetensors format

Eased resolution restriction: generated image's dimensions must be a multiple of 8 rather than 64

Now with a license!

Reorder elements in the UI from settings screen

Segmind Stable Diffusion support

Installation and Running

Make sure the required dependencies are met and follow the instructions available for:

NVidia (recommended)

AMD GPUs.

Intel CPUs, Intel GPUs (both integrated and discrete) (external wiki page)

Ascend NPUs (external wiki page)

Alternatively, use online services (like Google Colab):

List of Online Services

Installation on Windows 10/11 with NVidia-GPUs using release package

1. Download sd.webui.zip from v1.0.0-pre and extract its contents. 2. Run update.bat. 3. Run run.bat.

For more details see Install-and-Run-on-NVidia-GPUs

Automatic Installation on Windows

1. Install Python 3.10.6 (Newer version of Python does not support torch), checking "Add Python to PATH". 2. Install git. 3. Download the stable-diffusion-webui repository, for example by running git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git. 4. Run webui-user.bat from Windows Explorer as normal, non-administrator, user.

Automatic Installation on Linux

1. Install the dependencies:

BASH

# Debian-based:

sudo apt install wget git python3 python3-venv libgl1 libglib2.0-0 # Red Hat-based: sudo dnf install wget git python3 gperftools-libs libglvnd-glx # openSUSE-based: sudo zypper install wget git python3 libtcmalloc4 libglvnd # Arch-based: sudo pacman -S wget git python3

If your system is very new, you need to install python3.11 or python3.10:

BASH

# Ubuntu 24.04 sudo add-apt-repository ppa:deadsnakes/ppa sudo apt update sudo apt install python3.11 # Manjaro/Arch sudo pacman -S yay yay -S python311 # do not confuse with python3.11 package

# Only for 3.11 # Then set up env variable in launch script export python_cmd="python3.11" # or in webui-user.sh python_cmd="python3.11"

2. Navigate to the directory you would like the webui to be installed and execute the following command:

BASH

wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh

Or just clone the repo wherever you want:

BASH

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui

3. Run webui.sh. 4. Check webui-user.sh for options.

Installation on Apple Silicon

Find the instructions here.

Contributing

Here's how to add code to this repo: Contributing

Documentation

The documentation was moved from this README over to the project's wiki.

For the purposes of getting Google and other search engines to crawl the wiki, here's a link to the (not for humans) crawlable wiki.

Credits

Licenses for borrowed code can be found in Settings -> Licenses screen, and also in html/licenses.html file.

Stable Diffusion - https://github.com/Stability-AI/stablediffusion, https://github.com/CompVis/taming-transformers, https://github.com/mcmonkey4eva/sd3-ref

k-diffusion - https://github.com/crowsonkb/k-diffusion.git

Spandrel - https://github.com/chaiNNer-org/spandrel implementing

GFPGAN - https://github.com/TencentARC/GFPGAN.git

CodeFormer - https://github.com/sczhou/CodeFormer

ESRGAN - https://github.com/xinntao/ESRGAN

SwinIR - https://github.com/JingyunLiang/SwinIR

Swin2SR - https://github.com/mv-lab/swin2sr

LDSR - https://github.com/Hafiidz/latent-diffusion

MiDaS - https://github.com/isl-org/MiDaS

Ideas for optimizations - https://github.com/basujindal/stable-diffusion

Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.

Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)

Sub-quadratic Cross Attention layer optimization - Alex Birch (https://github.com/Birch-san/diffusers/pull/1), Amin Rezaei (https://github.com/AminRezaei0x443/memory-efficient-attention)

Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).

Idea for SD upscale - https://github.com/jquesnelle/txt2imghd

Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot

CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator

Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

xformers - https://github.com/facebookresearch/xformers

DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru

Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)

Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix

Security advice - RyotaK

UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC

TAESD - Ollin Boer Bohan - https://github.com/madebyollin/taesd

LyCORIS - KohakuBlueleaf

Restart sampling - lambertae - https://github.com/Newbeeer/diffusion_restart_sampling

Hypertile - tfernd - https://github.com/tfernd/HyperTile

Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.

(You)

About

Stable Diffusion web UI is an incredibly popular and feature-packed local web interface for the Stable Diffusion image generation AI

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Updated Jan 23, 2026

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