H100 vs V100

The FP16 dense performance reaches 989 TFLOPS on the H100 compared to 125 TFLOPS on the V100. This FP16 dense to FP16 dense ratio indicates the H100 can process substantially more operations per second during training and inference phases that rely on dense tensor computations. The FP32 figure of 67 TFLOPS on the H100 versus 15.7 TFLOPS on the V100 further widens the gap for precision sensitive workloads. Memory bandwidth of 3350 GB per second on the H100 versus 900 GB per second on the V100 directly influences sustainable batch sizes with the higher figure permitting larger batches before memory saturation occurs. FP16 with sparsity on the H100 measures 1979 TFLOPS while the V100 provides only the dense value of 125 TFLOPS so comparisons must remain within like categories. The TDP of 700 W on the H100 versus 300 W on the V100 reflects the power cost of these elevated throughput levels.

The H100 suits LLM training scenarios that require the FP16 dense rating of 989 TFLOPS and memory bandwidth of 3350 GB per second. Its 80 to 94 GB VRAM capacity also supports larger model states than the V100 alternative.

The V100 fits scientific computing tasks where the TDP of 300 W keeps power draw lower than the 700 W rating of the H100. Its FP32 performance of 15.7 TFLOPS remains adequate for established codes that do not demand the 67 TFLOPS available on the H100.