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Not an Apple guy, but I think an Apple M chip will run at ⅓ the speed of a top end RTX GPU, however it uses system memory, so it can easily be 32GB or 64Gb. That's pretty compelling, and if this is really a new class of application, NVidia is going to have to think about more memory for mainstream-ish products.

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It is 50x times slower on M1 than on RTX 3090.

M1 takes ~4.2s per iteration, 3.5 minutes per image [0].

RTX 3090 takes ~4.7s per image (all 50 iterations) [1].

[0] - https://wandb.ai/morgan/stable-diffusion/reports/Running-Sta...

[1] - trust me bro

Btw that's the kind of perf I see on my M1, but I keep seeing "0.00G VRAM used" for each generation. I wonder what that's about. In Activity Monitor I do see the GPU being used.

SD measures VRAM usage by calling a specific pyTorch method which usually wraps CUDA call.

I guess whomever ported that to M1 just haven’t implemented that method.

OK, I must have misread some comments. Thanks for the update.

This is a specialty application. I don't think it's going to be big enough to drive consumer technology like gaming?

Particularly since cloud services are likely to be competitive and work for anyone.

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