Google splits its eighth-generation TPU into two chips for training and inference

The TPU 8t targets massive pre-training runs while the TPU 8i is built for memory-hungry inference and reasoning workloads Google has stopped trying to build one AI chip that does everything. At Google Cloud Next on April 22, 2026, the company unveiled its eighth-generation Tensor Processing Units as two separate designs: the TPU 8t for large-scale pre-training and the TPU 8i for inference and high-concurrency reasoning. It marks the first time Google has split a TPU generation into distinct designs. The timing reflects where AI is heading. Google framed the launch around the so-called “agentic era,” where AI systems no longer just answer one prompt. They juggle many tasks at once, and that puts very different demands on hardware than training a model does. Two chips, two jobs Some quick vocabulary helps here. Training is when a model learns from enormous datasets, a process that rewards raw computing muscle at huge scale. Inference is when the finished model actually answers questions, which rewards memory, speed and cost efficiency because it happens constantly. The TPU 8t is the heavyweight. Google says it can scale to superpods of up to 9,600 chips, delivering 121 ExaFlops usin...