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AMD cards are fine from a raw performance perspective, but Nvidia has built themselves a moat of software/hardware features like ray-tracing, video encoding, CUDA, DLSS, etc where AMD's equivalents have simply not been as good.

With their current generation of cards AMD has caught up on all of those things except CUDA, and Intel is in a similar spot now that they've had time to improve their drivers, so it's pretty easy now to buy a non-Nvidia card without feeling like you're giving anything up.



AMD RT is still slower than Nvidia's.


I have no experience of using it so I might be wrong but AMD has ROCm which has something called HIP that should be comparable to CUDA. I think it also has a way to automatically translate CUDA calls into HIP as well so it should work without the need to modify your code.


Consumer card ROCm support is straight up garbage. CUDA support project was also killed.

AMD doesn't care about consumers anymore either. All the money in AI.


> AMD doesn't care about consumers anymore either. All the money in AI.

I mean, this also describes the quality of NVIDIA cards. And their drivers have been broken for the last two decades if you're not using windows.


AMD "has" ROCm just like Intel "has" AVX-512


`I think it also has a way to automatically translate CUDA calls`

I suspect the thing you're referring to is ZLUDA[0], it allows you to run CUDA code on a range of non NVidia hardware (for some value of "run").

[0] https://github.com/vosen/ZLUDA


For an extremely flexible value of "run" that you would be extremely unwise to allow anywhere near a project whose success you have a stake in.


To quote "The Dude"; "Well ... ummm ... that's ... ahh ... just your opinion man". There are people who are successfully running it in production, but of course depending on your code, YMMV.


it's mostly about AI training at this point. the software for this only supports CUDA well.




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