Googler here, if you haven’t looked at TPUs in a while check out the v5. They support PyTorch/JAX now, makes them much easier to use than TF only.
And that's all fixed capital expenditure - there's no risk a code bug or typo by an inexperienced student will lead to a huge bill.
Also, if you're looking for an alternative to CUDA because you dislike vendor lock-in, switching to something only available in GCP would be an absurd choice.
I've noticed this at companies. Yeah, the cloud is expensive, but you have a data center, and a few servers with RTX 3090s aren't expensive. A lot of research workloads can run on simple, cheap hardware.
Even older Nvidia P40s are still useful.
The H100s would be for businesses looking to get into this space.