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Summary
You’ll need a PC with a modern AMD or Intel processor, 16 gigabytes of RAM, an NVIDIA RTX GPU with 8 gigabytes of memory, and a minimum of 10 gigabytes of free storage space available. A GPU with more memory will be able to generate larger images without requiring upscaling.
Stable Diffusion is a popular AI-powered image generator that you can run on your own PC. But what are the minimum specs to run Stable Diffusion, and what components matter the most?
What PC Hardware Does Stable Diffusion Require?
The single most critical component for Stable Diffusion is your graphics card (GPU). Stable Diffusion — at least the primary version — runs almost exclusively on your GPU. That means that other system components, like yourCPU,RAM, and storage drives, don’t matter nearly as much.
Community forks sometimes change how Stable Diffusion operates and may result in a greater demand on your CPU and RAM than the official Stable Diffusion release.
Generally speaking, here are the minimums specs we’d recommend if you’re building a new PC with Stable Diffusion in mind:
Related:How to Run Stable Diffusion on Your PC to Generate AI Images
What Kind of Graphics Card (GPU) Do You Need to Run Stable Diffusion?
The Stable Diffusion community has worked diligently to expand the number of devices that Stable Diffusion can run on. We’ve seen Stable Diffusion running onM1 and M2 Macs, AMD cards, and old NVIDIA cards, but they tend to be difficult to get running and are more prone to problems. RTX NVIDIA GPUs are the only GPUs natively supported by Stable Diffusion at the time this article was written in December 2022.
Related:How to Check What Graphics Card (GPU) Is in Your PC
Any of the followingNVIDIA RTX cardswill work out of the box:
The RTX 3050 would work too, but it is difficult to recommend given how it is priced compared to the RTX 3060 12 gigabyte variant.
Try to buy the newest GPU you can. Any of the 20, 30, or 40-series GPUs with 8 gigabytes of memory from NVIDIA will work, but older GPUs — even with the same amount ofvideo RAM (VRAM)— will take longer to produce the same size image. If you’re building or upgrading a PC specifically with Stable Diffusion in mind, avoid the older RTX 20-series GPUs unless you find a fantastic deal on one, since they’re significantly slower.
How Much Video Memory (GPU Memory) Do You Need?
The larger you make your images, the more VRAM Stable Diffusion will use. Theminimumamount of VRAM you should consider is 8 gigabytes.
The unmodified Stable Diffusion releasewill produce 256x256 images using 8 GB of VRAM, but you will likely run into issues trying to produce 512x512 images. If you want to go to 512x512 images without fiddling with the settings, get a GPU with 12 gigabytes of VRAM or more.
TheRTX 3060is a potential option at a fairly low price point. The RTX 3060 is slower than the3060 Ti, however, the RTX 3060 has 12 gigs of VRAM, whereas the 3080 Ti only has 8 gigs. The extra VRAM will really shine in Stable Diffusion, but that comes at the expense of speed and gaming performance.
MSI Gaming GeForce RTX 3060
A GeForce RTX GPU with 12GB of RAM for Stable Diffusion at a great price.
Related:Does GPU Memory Matter? How Much VRAM Do You Need?
When it comes toadditional VRAMand Stable Diffusion, the sky is the limit — Stable Diffusion will gladly use every gigabyte of VRAM available onan RTX 4090. It all depends on the size of the image you’re generating.
Of course, there are all sorts of optimizedforksthat allow you to get away with much less VRAM at the expense of speed, but if you want to be sure it’ll work, stick with RTX NVIDIA cards that have at least 8 gigabytes of memory.
Should You Use an Optimized Fork of Stable Diffusion?
In a word: Yes.
The Stable Diffusion community has done a fantastic job expanding the number of supported GPUs to make Stable Diffusion more accessible.
Community forks often include a user interface, additional models to refine your creations, and optimizations that allow you to generate larger images with less VRAM. Some users have been able to generate 512x512 images with as little as 4 gigabytes of VRAM using community forks. The same optimizations allow users with 8 and 12 gigabyte GPUs to produce significantly larger images.
Theuser interface is a great feature too, as it makes using Stable Diffusioneasier. It makesgenerating AI video with Stable Diffusionpossible too.
Related:How to Run Stable Diffusion Locally With a GUI on Windows
Just be careful. Most of the modifications you’ll find are written by well-intentioned enthusiasts, but there is always the possibility that someone is acting maliciously. If yourantivirusflags a Stable Diffusion fork as malicious, don’t ignore it. Stable Diffusion is not known for producing false positives from antivirus software, so any warnings you receive should be taken seriously.
Once you’ve got the right hardware, you’re able to spend timeoptimizing your Stable Diffusion promptsinstead of your PC.
