H100 vs MI250X

Dense FP16 performance on the H100 measures 989 TFLOPS against 383 TFLOPS on the MI250X. This ratio indicates the H100 completes dense FP16 operations more than twice as fast. The FP32 figures show 67 TFLOPS for the H100 versus 47.9 TFLOPS for the MI250X. Training workloads that rely on dense FP16 therefore finish in less time on the H100. Inference tasks using the same dense FP16 precision also benefit from the higher throughput. Memory bandwidth of 3350 GB per second on the H100 compared with 3277 GB per second on the MI250X allows marginally larger batch sizes before memory saturation occurs. The H100 TDP of 700 W exceeds the MI250X TDP of 560 W so power limited environments may constrain sustained dense FP16 operation on the H100.

The H100 suits workloads that require the highest dense FP16 throughput of 989 TFLOPS. Its 67 TFLOPS FP32 rating also exceeds the MI250X rating of 47.9 TFLOPS. Organizations running dense tensor operations at scale therefore select the H100 when raw compute speed takes priority over memory capacity.

The MI250X suits workloads that require 128 GB of memory rather than the 80 to 94 GB available on the H100. Its TDP of 560 W remains lower than the 700 W TDP of the H100. Teams that prioritize memory headroom over dense FP16 speed of 383 TFLOPS therefore select the MI250X.