GH200 vs RTX 3090

The FP16 dense performance reaches 989 TFLOPS in the GH200 compared to 71 TFLOPS dense FP16 in the RTX 3090. This ratio indicates that the GH200 can process larger models or achieve faster iteration times during training and inference tasks that utilize dense FP16 operations. The FP32 figure of 67 TFLOPS in the GH200 exceeds the 35.6 TFLOPS in the RTX 3090. Memory bandwidth of 4000 GB/s versus 936 GB/s allows the GH200 to support larger batch sizes in memory intensive operations without frequent data transfers. Sparse FP16 performance measures 1979 TFLOPS in the GH200 and 142 TFLOPS in the RTX 3090. Direct comparison of these sparse figures shows the advantage in scenarios where sparsity techniques apply. The higher bandwidth in the GH200 facilitates handling of extensive datasets within the 96 GB VRAM limit relative to the 24 GB in the RTX 3090.

The GH200 serves as the better choice when workloads demand the 96 GB HBM3 memory capacity and the 4000 GB/s bandwidth. These specifications enable processing of models that exceed the 24 GB limit of the RTX 3090. Compute capabilities including 989 TFLOPS dense FP16 and 67 TFLOPS FP32 further support intensive numerical operations in scientific contexts.

The RTX 3090 serves as the better choice for workloads that fit within 24 GB GDDR6X VRAM and require only 350W TDP. Its 71 TFLOPS dense FP16 and 35.6 TFLOPS FP32 remain adequate for smaller scale tasks. The PCIe form factor and PCIe 4.0 interconnect align with standard server configurations that do not need SXM or NVLink-C2C.