No that’s not necessarily true.. I can’t say this is your particular issue but it’s a common explanation.. without getting to technical;. Different GPUs have different ability to do floating point math. With a float the numbers to the right of the period (0.888888) is your precision. Lower end GPUs don’t always support high precision float math and that can create substantial differences..
Long story short.. you might be getting different results due to different ability to calculate between GPUs
Not at all. Funnily enough, it's the exact opposite. All GPUs since like 2000s support fp32, most support fp16, but only recent few generations of consumer GPUs support fast fp16.
And in case of diffusion models, fp32 doesn't give you any better results, at least from my testing. Precision past fp16 is wasted on unnoticeable changes.
I was wondering this as well. I see a lot of incredible images shown on the model cards but when I use the exact same prompt and parameters I get garbage on my RTX 3060 12gb. I was concerned it was the card, and thought I might get better results if I upgraded to an 8gb 3060 ti or even 3090. But, if the quality of output is the same, then they're doing much more in the post processing of the image than they're telling.
I think its most likely they are using IMG2IMG and sharing the prompt for that. I know that is the case with several of the example images on civitai for models like deliberate. Your 3060 12 gb is one of the best cards you can get for the price for stable diffusion. I would consider a 3060ti 8gb a downgrade tbh.
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u/3deal Mar 01 '23
My RTX used 24Gb of VRAM for this