A100 remains in deployed AI infrastructure. H100 adds Hopper's Transformer Engine and newer interconnect options. An upgrade decision depends on the model, software stack, and the actual servers you can buy.
What to compare
Check memory capacity, precision support, GPU-to-GPU interconnect, and power on the exact SKUs. A100 comes in multiple memory and form-factor variants. H100 PCIe and H100 SXM also differ. Do not compare a bare A100 card price with a complete HGX H100 server quote.
NVIDIA's H100 product specifications list the supported H100 variants. Its HGX reference architecture lists 80 GB HBM3 for H100 SXM in an eight-GPU node.
Test your workload
Benchmark the same model, precision, framework, batch size, and GPU count on both systems. Check whether your code uses FP8, how much memory it needs, and whether it is limited by compute, memory bandwidth, or networking. A general speedup claim cannot replace this test.
For an existing A100 fleet, include migration effort, server compatibility, support, and utilization in the decision. A newer GPU may be useful when it finishes enough additional work to justify the full installed cost.
Compare current written prices and delivery dates for complete A100 and H100 systems. Send your workload, GPU count, destination, and target date to compare available systems.
