MI300X vs RTX 5090

The MI300X FP16 dense rating of 1307.4 TFLOPS exceeds the RTX 5090 FP16 dense rating of 209.5 TFLOPS by a factor derived directly from those two numbers. The same pattern holds for FP16 with sparsity where the MI300X reaches 2614.9 TFLOPS and the RTX 5090 reaches 419 TFLOPS. Higher memory bandwidth of 5300 GB/s on the MI300X versus 1792 GB/s on the RTX 5090 supports larger batch sizes during training or inference workloads that move substantial activation data. FP32 performance follows a similar ratio with the MI300X at 163.4 TFLOPS and the RTX 5090 at 104.8 TFLOPS. These dense versus dense and sparsity versus sparsity comparisons indicate that the MI300X sustains greater throughput on identical numeric formats without mixing dense and sparsity figures.

The MI300X suits workloads that require 192 GB HBM3 memory and 5300 GB/s bandwidth such as large scale model training. Its 1307.4 TFLOPS dense FP16 rating and Infinity Fabric interconnect further support multi GPU scaling where memory capacity limits batch size on smaller devices.

The RTX 5090 suits deployments that prioritize the 575 W TDP and PCIe form factor over maximum memory capacity. Its 32 GB GDDR7 memory and 1792 GB/s bandwidth remain adequate for inference tasks that fit within those limits while the lower power draw reduces cooling requirements.