GPUEater do, i think. Right now, though, they are a viable option for an on-premise use case where you have a budget of say a $100k dollars or more and need a huge amount of compute and have larger models to train. The Vega R7 gives you 16GB Ram (11GB in the 2080Ti) and is just slightly lower performance than the 2080Ti (322 vs 302 images/sec for resnet-50 from here: https://www.youtube.com/watch?v=neb1C6JlEXc ). And you have servers with PCI-4.0 support, so that distributed training scales (yes, 2080-Ti supports nvlink, but nvlink servers cost way more). Simple math example. A PCI-4.0 server with 256GB Ram and 8xVegaR7 should cost around $10K. With a couple of switches and racks, you can get 100s of GPUs for just a couple of hundred thousand dollars (note, only 2 GPU servers per rack for now is normal, otherwise you have to buy non-commodity racks with high power draw).

What would you want it for over nvidia in the cloud?

Testing if nothing else, I'd you are shipping to be people running AMD GPUs then that would be useful without having to buy a card and another machine for it to go in