MI300X vs H100

The MI300X FP16 dense rating of 1307.4 TFLOPS exceeds the H100 FP16 dense rating of 989 TFLOPS by a ratio of 1.32 to 1 while the MI300X FP16 with sparsity rating of 2614.9 TFLOPS exceeds the H100 FP16 with sparsity rating of 1979 TFLOPS by the same ratio. This difference translates into shorter iteration times during training loops that rely on dense FP16 operations and into higher token throughput during inference that relies on dense FP16 operations. The MI300X memory bandwidth of 5300 GB/s exceeds the H100 bandwidth of 3350 GB/s allowing larger batch sizes before memory capacity of 192 GB becomes the limit. The MI300X FP32 rating of 163.4 TFLOPS exceeds the H100 FP32 rating of 67 TFLOPS supporting faster execution of mixed precision workloads that fall back to FP32 accumulation.

The MI300X suits workloads that require the full 192 GB HBM3 capacity such as training of models whose parameters exceed 80 GB. Its 5300 GB/s bandwidth supports sustained data movement for large batch sizes in LLM training. The 1307.4 TFLOPS FP16 dense rating further accelerates these operations compared with alternatives.

The H100 suits deployments that operate within existing NVIDIA software stacks and that fit inside the 80 to 94 GB memory envelope. Its 700 W TDP rating provides a lower power draw than 750 W while still delivering 989 TFLOPS FP16 dense performance for inference tasks.