CivArchive
    Preview 7414024
    Preview 7414179
    Preview 7414505
    Preview 7414800
    Preview 7414967
    Preview 7415183
    Preview 7415364
    Preview 7415450
    Preview 7415510
    Preview 7415755
    Preview 7414603
    Preview 7414856
    Preview 7414715
    Preview 7414449
    Preview 7416148
    Preview 7415841
    Preview 7415969
    Preview 7416202
    Preview 7416254
    Preview 7416019

    Hires. fix

    from 552x616 to 1104x1232

    NEW HERE:

    https://github.com/lllyasviel/stable-diffusion-webui-forge

    Stable Diffusion WebUI Forge

    Stable Diffusion WebUI Forge is a platform on top of Stable Diffusion WebUI (based on Gradio) to make development easier, optimize resource management, and speed up inference.

    The name "Forge" is inspired from "Minecraft Forge". This project is aimed at becoming SD WebUI's Forge.

    Compared to original WebUI (for SDXL inference at 1024px), you can expect the below speed-ups:

    1. If you use common GPU like 8GB vram, you can expect to get about 30~45% speed up in inference speed (it/s), the GPU memory peak (in task manager) will drop about 700MB to 1.3GB, the maximum diffusion resolution (that will not OOM) will increase about 2x to 3x, and the maximum diffusion batch size (that will not OOM) will increase about 4x to 6x.

    2. If you use less powerful GPU like 6GB vram, you can expect to get about 60~75% speed up in inference speed (it/s), the GPU memory peak (in task manager) will drop about 800MB to 1.5GB, the maximum diffusion resolution (that will not OOM) will increase about 3x, and the maximum diffusion batch size (that will not OOM) will increase about 4x.

    3. If you use powerful GPU like 4090 with 24GB vram, you can expect to get about 3~6% speed up in inference speed (it/s), the GPU memory peak (in task manager) will drop about 1GB to 1.4GB, the maximum diffusion resolution (that will not OOM) will increase about 1.6x, and the maximum diffusion batch size (that will not OOM) will increase about 2x.

    4. If you use ControlNet for SDXL, the maximum ControlNet count (that will not OOM) will increase about 2x, the speed with SDXL+ControlNet will speed up about 30~45%.

    Another very important change that Forge brings is Unet Patcher. Using Unet Patcher, methods like Self-Attention Guidance, Kohya High Res Fix, FreeU, StyleAlign, Hypertile can all be implemented in about 100 lines of codes.

    Thanks to Unet Patcher, many new things are possible now and supported in Forge, including SVD, Z123, masked Ip-adapter, masked controlnet, photomaker, etc.

    No need to monkeypatch UNet and conflict other extensions anymore!

    Forge also adds a few samplers, including but not limited to DDPM, DDPM Karras, DPM++ 2M Turbo, DPM++ 2M SDE Turbo, LCM Karras, Euler A Turbo, etc. (LCM is already in original webui since 1.7.0).

    Finally, Forge promise that we will only do our jobs. Forge will never add unnecessary opinioned changes to the user interface. You are still using 100% Automatic1111 WebUI.

    Settings I used for model

    To load target model

    SDXLClipModel

    Sampling Steps40-50

    CFG scale: 7-20

    Sampling Method: DPM++ 3M SDE Exponential+DPM++ 2M SDE Turbo

    Ratio:1024x1024

    Description

    FAQ

    Checkpoint
    SDXL 1.0

    Details

    Downloads
    247
    Platform
    CivitAI
    Platform Status
    Available
    Created
    3/3/2024
    Updated
    8/28/2026
    Deleted
    -

    Files

    realStableXL_realStableA.safetensors

    Mirrors

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.