Google has done stuff primarily for negotiation purposes (e.g. POWER9 chips) but TPU ain't one. It's not a backup option or presumed "inferior solution" to NVIDIA. Their entire ecosystem is TPU-first.
Pretty sure the answer is yes. I have no direct knowledge of the matter for Gemini 2.5, but in general TPUs were widely used for training at Google. Even Apple used them to train their Apple Intelligence models. It’s not some esoteric thing to train on TPU; I would consider using GPU for that inside Google esoteric.
P.S. I found an on-the-record statement re Gemini 1.0 on TPU:
"We trained Gemini 1.0 at scale on our AI-optimized infrastructure using Google’s in-house designed Tensor Processing Units (TPUs) v4 and v5e. And we designed it to be our most reliable and scalable model to train, and our most efficient to serve."
lostmsu|10 months ago
mmx1|10 months ago
P.S. I found an on-the-record statement re Gemini 1.0 on TPU:
"We trained Gemini 1.0 at scale on our AI-optimized infrastructure using Google’s in-house designed Tensor Processing Units (TPUs) v4 and v5e. And we designed it to be our most reliable and scalable model to train, and our most efficient to serve."