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Optimum SDXL Usage
ClashSAN edited this page Dec 15, 2023
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Here's a quick listing of things to tune for your setup:
- Nvidia (12gb+)
--xformers
- Nvidia (8gb)
--medvram-sdxl --xformers
- Nvidia (4gb)
--lowvram --xformers
- AMD (4gb)
--lowvram --opt-sub-quad-attention
+ TAESD in settingsBoth rocm and directml will generate at least 1024x1024 pictures at fp16. If your AMD card needs --no-half, try enabling --upcast-sampling instead, as full precision sdxl is too large to fit on 4gb.
- (Windows) Not all nvidia drivers work well with stable diffusion. All drivers above version 531 can cause extreme slowdowns on Windows when generating large images towards, or above your card's maximum vram. To mitigate this potential speed degradation, follow the steps outlined by nvidia on their website. https://nvidia.custhelp.com/app/answers/detail/a_id/5490 Related issues: (vladmandic/automatic/discussions/1285), (#11063).
- (Linux) install
tcmalloc
, greatly reducing RAM usage:sudo apt install --no-install-recommends google-perftools
(#10117). - Add a pagefile/swapfile to prevent failure loading weights due to low RAM.
- Use an SSD for faster load time, especially if a pagefile is required.
- Have at least 24gb ram on Windows 11, and at least 16gb on Windows 10
- Use sdxl-vae-fp16-fix; a VAE that will not need to run in fp32. This will increase speed and lessen VRAM usage at almost no quality loss.
- Use TAESD; a VAE that uses drastically less vram at the cost of some quality.
This is the Stable Diffusion web UI wiki. Wiki Home
Setup
- Install and run on NVidia GPUs
- Install and run on AMD GPUs
- Install and run on Apple Silicon
- Install and run on Intel Silicon (external wiki page)
- Install and run via container (i.e. Docker)
- Run via online services
Reproducing images / troubleshooting
Usage
- Features
- Command Line Arguments and Settings
- Optimizations
- Custom Filename Name and Subdirectory
- Change model folder location e.g. external disk
- User Interface Customizations
- Guides and Tutorials
Developers