sd-extension-system-info
System and platform info and standardized benchmarking extension for SD.Next and WebUI (by vladmandic)
stable-diffusion.cpp
Stable Diffusion in pure C/C++ (by leejet)
| sd-extension-system-info | stable-diffusion.cpp | |
|---|---|---|
| 51 | 10 | |
| 262 | 2,662 | |
| - | - | |
| 6.7 | 8.8 | |
| 7 days ago | 3 days ago | |
| Python | C++ | |
| 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.
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
stable-diffusion.cpp
Posts with mentions or reviews of stable-diffusion.cpp.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-08.
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I've open sourced my Flutter plugin to run on-device LLMs on any platform. TestFlight builds available now.
I did start with integrating SD with this repo: https://github.com/leejet/stable-diffusion.cpp
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Stable Diffusion in pure C/C++
Interesting. It still doesn't seem to be very quick: https://github.com/leejet/stable-diffusion.cpp/issues/6
But don't get me wrong, I look forward to playing with ggml SD and its development.
- StableDiffusion CPP
- Stable-Diffusion.cpp
What are some alternatives?
When comparing sd-extension-system-info and stable-diffusion.cpp you can also consider the following projects:
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️
tomesd - Speed up Stable Diffusion with this one simple trick!
ggml - Tensor library for machine learning
voltaML-fast-stable-diffusion - Beautiful and Easy to use Stable Diffusion WebUI
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-amdgpu - Stable Diffusion web UI
root - The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
scribble-diffusion - Turn your rough sketch into a refined image using AI
seed-alchemy - Frontend UI and Backend Server for Stable Diffusion models
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
vit.cpp - Inference Vision Transformer (ViT) in plain C/C++ with ggml
sd-extension-system-info vs automatic
stable-diffusion.cpp vs tinygrad
sd-extension-system-info vs tomesd
stable-diffusion.cpp vs ggml
sd-extension-system-info vs voltaML-fast-stable-diffusion
stable-diffusion.cpp vs stable-diffusion-webui
sd-extension-system-info vs stable-diffusion-webui-amdgpu
stable-diffusion.cpp vs root
sd-extension-system-info vs scribble-diffusion
stable-diffusion.cpp vs seed-alchemy
sd-extension-system-info vs HIP
stable-diffusion.cpp vs vit.cpp