H200 vs RTX 2080

The FP16 dense figure of 989 TFLOPS on the H200 exceeds the FP16 dense figure of 40.3 TFLOPS on the RTX 2080 by a wide margin and this gap affects training and inference workloads that rely on half precision. The FP16 with sparsity figure of 1979 TFLOPS on the H200 likewise exceeds the dense FP16 figure of 40.3 TFLOPS on the RTX 2080. Memory bandwidth of 4800 GB/s on the H200 supports larger batch sizes than the 448 GB/s on the RTX 2080. The FP32 figure of 67 TFLOPS on the H200 compared with 10 TFLOPS on the RTX 2080 further widens the difference for workloads that stay in single precision.

The H200 suits workloads that require 141 GB HBM3e VRAM and 4800 GB/s memory bandwidth such as large scale training. Its FP16 dense performance of 989 TFLOPS and FP8 dense performance of 1979 TFLOPS enable faster iteration on models that fit within the higher capacity. The 700W TDP is acceptable when power delivery supports SXM or NVL form factors.

The RTX 2080 suits workloads that fit within 8-11 GB GDDR6 VRAM and require only 215W TDP. Its FP32 performance of 10 TFLOPS remains adequate for lighter inference tasks that do not demand the 989 TFLOPS FP16 dense rating of the H200. PCIe form factor and 448 GB/s bandwidth align with systems that lack support for NVLink or InfiniBand.