H100 vs RTX 5080

The FP16 dense to FP32 ratio reaches 989 TFLOPS divided by 67 TFLOPS on the H100 while the RTX 5080 shows 112.6 TFLOPS divided by 56.3 TFLOPS. This delta indicates greater acceleration potential for mixed precision operations during training and inference on the H100. Memory bandwidth of 3350 GB/s on the H100 compared with 960 GB/s on the RTX 5080 supports larger batch sizes in memory intensive tasks. Dense FP16 performance on the H100 at 989 TFLOPS exceeds the RTX 5080 dense FP16 figure of 112.6 TFLOPS by a factor derived directly from these values. Sparse FP16 on the H100 reaches 1979 TFLOPS against 225.1 TFLOPS on the RTX 5080 under the same sparsity condition.

The H100 suits scenarios requiring 80 to 94 GB HBM3 memory and 3350 GB/s bandwidth for large scale models. Its 989 TFLOPS dense FP16 and NVLink interconnect enable handling of workloads beyond the 16 GB GDDR7 limit of the RTX 5080. Form factors including SXM5 and NVL further support deployment in multi GPU configurations with InfiniBand.

The RTX 5080 fits environments constrained by 360W TDP and PCIe form factor alone. Its 112.6 TFLOPS dense FP16 and 960 GB/s bandwidth suffice for tasks that do not exceed 16 GB VRAM capacity. Lower power draw relative to the 700W H100 reduces infrastructure demands in single GPU setups.