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by ISV_Damocles 241 days ago
Most of the big OSS AI codebases (LLM and Diffusion, at least) have code to work on any GPU, not just nVidia GPUs, now. There's a slight performance benefit to sticking with nVidia, but once you need to split work across multiple GPUs, you can do a cost-benefit analysis and decide that, say, 12 AMD GPUs is faster than 8 nVidia GPUs and cheaper, as well.

Then nVidia's moat begins to shrink because they need to offer their GPUs at a somewhat reduced price to try to keep their majority share.
2 comments
lmeyerov 241 days ago
Share can go up and down if consumption keeps going up crazily. We now spend more per dev on their personal use inferencing providers than their home devices, so inferencing chips are effectively their new personal computers...
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epolanski 241 days ago
> There's a slight performance benefit to sticking with nVidia

In training, not in inference and not in perf/$.

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