H200 vs T4

The difference in dense FP16 performance between 989 TFLOPS on the H200 and 65 TFLOPS on the T4 translates to substantially higher throughput for training and inference operations. Memory bandwidth of 4800 GB/s versus 320 GB/s allows the H200 to support larger batch sizes in memory intensive applications. The FP32 dense rating of 67 TFLOPS on the H200 exceeds the 8.1 TFLOPS on the T4 by a wide margin. With sparsity the H200 reaches 1979 TFLOPS in FP16 while the T4 lacks a published sparse figure. Power consumption at 700 W for the H200 and 70 W for the T4 influences deployment choices in efficiency focused environments. These metrics indicate the H200 handles complex models more effectively. The INT8 dense rating of 1979 TOPS on the H200 further separates it from the 130 TOPS on the T4 for quantized workloads.

The H200 suits scenarios that require 141 GB HBM3e memory and 989 TFLOPS dense FP16 for large model training. Its 4800 GB/s bandwidth supports extensive batch processing that exceeds the capabilities of the T4 with 16 GB and 320 GB/s. Users select the H200 when FP32 dense performance at 67 TFLOPS becomes necessary for scientific simulations.

The T4 fits deployments limited to 70 W TDP and PCIe form factors for basic inference tasks. Its 65 TFLOPS dense FP16 and 16 GB GDDR6 handle smaller workloads where the 700 W draw of the H200 proves excessive. The T4 serves edge environments that prioritize the 8.1 TFLOPS FP32 rating over higher throughput options.