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How large an image will this handle (versus how much RAM you have)?

It seems the GPU memory requirements beyond 512x512 are obscene.



I'm on a iMac M1 16gb and I can handle up to 768x768 but since it's shared memory I close out every other application and run things overnight.

The biggest issue with apple chips is that the --seed setting doesn't work. I should be able to set a seed to, for instance, 1083958 and if I re-run a command at the same resolution with that seed, I should get the same image every time. This would allow me to test different steps so I could generate a 100 images at 16 steps (which is quite fast) and pick the ones that are most promising and re-render at 64 or 128 steps.

But currently you can't do that on apple hardware because of an open issue in PyTorch. Genuinely hoping a fix comes soon, until it is this is more of a novelty than a tool on Apple hardware.


There's a partial fix for the seed issue on Reddit.


I can't seem to find it, do you have a link?



Me at the end of last year: "Should I really go for the full 64GB on this M1 Pro? What could I possibly use this for? mmbml mumble... something about unified GPU... something Deep Learning, one day..."

Me now: "a red juicy apple floating in outer space, like a planet" --H 768 --W 768

Uses about 27GB. 1.81s/it.

Can't do 1024x1024 yet because of some hardcoded Metal issue (https://github.com/pytorch/pytorch/issues/84039.


I was so geniunely happy with my 16GB iMac M1 until stable-diffusion released.

I was amazed at how fast and powerful it was. I thought this meant I could stop buying top-of-the-line Macs every 4 years and start buying bottom-of-the-line Macs every 5 years. And that would have been 100% true... if it weren't for stable-diffusion.


This model was mostly trained on 512x512 so you should stick to approximately that size.

Use external upscalers like RealESRGAN, SwinIR or BSRGAN or GFPGAN (faces).

Alternatively use hacks like txt2imghd to get it to natively create 1 MP images.


Most people that want hires would just feed the resulting image into AI upscaler like gigapixel.




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