5 ms·
I'm running 1660 ti on Windows 11. I'm thinking about getting a 3090 so that I can make higher resolution images. Gfpgan runs much faster for me 5 seconds per
by gitfan86 4y ago
I'm running 1660 ti on Windows 11.
I'm thinking about getting a 3090 so that I can make higher resolution images.
Gfpgan runs much faster for me 5 seconds per picture
- machineleaning 4y agoWhat resolution could you get on a 3090?
- gitfan86 4y agoNo idea, things are changing very quickly now
- BatteryMountain 4y agoGood way to know (if not found online) is to start at 512x512 if you have a card with 12GB VRAM and try to increment it (the ui slider increases it by 64px for each increment) and backtrack when you start getting "cuda out of memory" errors. I've seen some renders on discord where the sizes are well above 1000px, so they must have had a 16/24GB cards or something similar. In the research context, they are used to using 40GB/80GB hardware (and perhaps multiples) to train and render. So quite remarkable that it works on consumer hardware at this point. edit: on second thought, they most likely rendered at 512px but then ran it through an upscaler model. I've been meaning to hook mine up but kinda forgot to try.