tomesd
Speed up Stable Diffusion with this one simple trick! (by dbolya)
sd-extension-system-info
System and platform info and standardized benchmarking extension for SD.Next and WebUI (by vladmandic)
| tomesd | sd-extension-system-info | |
|---|---|---|
| 18 | 51 | |
| 1,207 | 258 | |
| - | - | |
| 5.4 | 9.3 | |
| 5 months ago | 3 months ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tomesd
Posts with mentions or reviews of tomesd.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-11.
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List of all the ways to improve performance for stable diffusion.
They show up to 5.4 times greater: you can see his results in the image on the github repo here: https://github.com/dbolya/tomesd
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Question about automatic1111 set up after changing gpu
Another optimization extension you can use as well is token merging which has reported around 5.4x faster image generation.
- +39%~51% faster at the cost of some details? ToMe officially arrives to Auto1111's webui v1.3.0
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AUTOMATIC1111 updated to 1.3.0 version
It merges redundant tokens: https://github.com/dbolya/tomesd So it can make the generation slightly faster.
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I made some changes in AUTOMATIC1111 SD webui, faster but lower VRAM usage
Mods patched - Tomesd - Pillow-SIMD - OpenCV-CUDA (WIP) - Removed some unused imports and startup checking - Improved performance with reduced VRAM usage (tested on txt2img only) - Added a new option to use external RealESRGAN with --external-realesrgan
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Honest question, how are people getting ~35-40 it/sec on 4090? My spits 20 at most
Were the 40 it/s perhaps achieved with ToMe?
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Vlad diffusion keeps growing. Big thanx to all supporters :)
Done! Proposal
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Token Merging actually works and reduces generation time as well as RAM
This feature comes from this project: https://github.com/dbolya/tomesd
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How can I squeeze every ounce of performance from web UI?
GitHub - dbolya/tomesd: Speed up Stable Diffusion with this one simple trick!
- Token Merging for Fast Stable Diffusion
sd-extension-system-info
Posts with mentions or reviews of sd-extension-system-info.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-19.
- RTX 4070 vs rx 7800 xt
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AMD for AI
I've been using both SD and various LLM on linux without any issue and have done so for months. Windows support is also starting to roll out slowly, with koboldcpp-rocm recently giving me 20-25+t/s for a13B even on windows. you can see what SD performance is like on sites like these. those numbers roughly match what i get on my RX6800 as well (8t/s).
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Stable Diffusion in pure C/C++
That seems a lot worse than a 2060 SUPER with PyTorch in A1111.
https://vladmandic.github.io/sd-extension-system-info/pages/... (search for 2060 SUPER)
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Iterations per second benchmarking question
But usually A1111 users use benchmark on this extension https://github.com/vladmandic/sd-extension-system-info
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Best AMD SD Guide for 2023?
AMD SD = Setup Diaster? it was quite troublesome googling the few linux/amdgpu/rocm/sd vers/configs/params posts online. Also the whole PC may hang during generation which is bad for the harddisk. Your card is way more powerful so may not hang like mine. People are getting 8it/s https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html
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Which one is better? Nvidia Tesla M40 vs Nvidia Tesla P4?
According to system info benchmark, M40 is like 1-2 it/s and P4 is barely better than that.
- Video card price/performance ratio
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--medvram. Should I remove this flag? Running 3090
Anyway to properly "benchmark" the impacts different switches on your image generation speed, it is better to use the benchmarking utility from extension https://github.com/vladmandic/sd-extension-system-info (it also creates a very handy table of results from other users at https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html for you to compare with.
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Searching for install guide for top performance setup on WSL2 (Automatic1111)
I can see that the top performance benchmark results on SD WebUI Benchmark Data (using RTX 4090), are obtained through WSL2 running Automatic1111 on a Linux dist and Python 3.10.11, along with PyTorch 2.1.0.dev+cu121 (like benchmark id: 4126)
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Advice for Optimization on an RTX 8000
You should be able to compare based on the published benchmarks, just replicate the settings based on what's reported https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html
What are some alternatives?
When comparing tomesd and sd-extension-system-info you can also consider the following projects:
stable-diffusion-webui-ux - Stable Diffusion web UI UX
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
voltaML-fast-stable-diffusion - Beautiful and Easy to use Stable Diffusion WebUI
stable-diffusion-webui-tensorrt
stable-diffusion-webui-directml - Stable Diffusion web UI
scribble-diffusion - Turn your rough sketch into a refined image using AI
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
stable-diffusion-webui-directml - Stable Diffusion web UI
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️
tomesd vs stable-diffusion-webui-ux
sd-extension-system-info vs automatic
tomesd vs ComfyUI
sd-extension-system-info vs voltaML-fast-stable-diffusion
tomesd vs stable-diffusion-webui-tensorrt
sd-extension-system-info vs stable-diffusion-webui-directml
tomesd vs automatic
sd-extension-system-info vs scribble-diffusion
tomesd vs diffusers
sd-extension-system-info vs HIP
tomesd vs stable-diffusion-webui-directml
sd-extension-system-info vs tinygrad