Which AI chip fits which workload?

This guide compares the major AI accelerators a buyer, builder, or analyst will hear about: Nvidia H100, H200, B200, GB300, Google TPU, AWS Trainium, AMD MI300X, Huawei Ascend 910C, and Groq.

• Training: prioritise cluster scale, networking, software maturity, HBM capacity, and availability.
• Inference: prioritise latency, memory bandwidth, KV-cache economics, batching, and ecosystem fit.
• Procurement: the best chip on paper can lose to the chip you can actually buy, power, and support.