Google Splits Its AI Chip. Here’s Why It Matters For Enterprises

At Google Cloud Next, Google unveiled separate eighth-generation TPUs: TPU-8t for training and TPU-8i for inference and agentic workloads.

TPU-8i was designed around latency, memory, and network topology, while TPU-8t is optimized for throughput.

The split design shows AI infrastructure is diverging between training and low-latency inference from the ground up.

That shift is likely to shape cloud costs, performance tradeoffs, and enterprise architecture decisions.