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Comment by dr_dshiv | Hacker News Reader

How much VRAM was previously required?

Looks like 10GB in the README[0] for a 512x512 image - though the fork[1] from the repo in this PR claims to be able to work with as little as 4GB VRAM.

[0] https://github.com/CompVis/stable-diffusion#stable-diffusion [1] https://github.com/basujindal/stable-diffusion#txt2img

I can generate a 768x896 pixels image on an RTX 3090, using 23.4/24GB

How does the content of the images look compared to the same prompt and seed for 512x512? I ask because when I make 768x896 with M1 MAX the resulting image is less coherent, more noisy, and or has repeating subject matter, nothing really usable unlike 512x512.

Same here.

I am able to generate a maximum resolution of 512x768 on my 11GB 1080Ti. This seems to use almost 100% of the available RAM.

That's weird. I cap out at 512x512 on my 16GB Ampere card. Even stepping down precision doesn't help. I wonder what's different.

I use it directly from Python.

Perhaps a different kind of chipset that isn’t optimized yet? Just a guess based on other graphics processes.

You might have the n_samples (aka batch size) set to a number greater than 1? That basically multiplies the amount of VRAM you’re using.

I can generate a 512x512 on my 10gb 3080 no problem (or three 384x384 at a time)

Try the hlky fork: https://github.com/hlky/stable-diffusion

It measures memory usage as well.

512x706 on rtx 2060s with 8gb vram

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