I think you underestimate the challenge in programming TensorFlow to use Tensor-cores, currently. It is a hell of a lot of fp16 and fp32 casts, and, frankly, mo

I think you underestimate the challenge in programming TensorFlow to use Tensor-cores, currently. It is a hell of a lot of fp16 and fp32 casts, and, frankly, most Python programmers / Data Scientists do not have the skills to do it. There is some work in getting TensorFlow to automatically do it for you, but i haven't seen the evidence in benchmarks, yet. From this thread, it looks like (for Resnet-50), the Radeon VII is closing in on the nvidia 2080Ti - with more memory (16 vs 11 GB), can be used in a data-center EULA, and 2/3 of the price. https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/173 https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/... In any case, Google are not going the tensorcores route with TPUs. Fast general purpose matmuls. Same as AMD. I don't think tensorcores is a clear winner, yet.