A100 vs MI300X

FP16 dense performance on the MI300X reaches 1307.4 TFLOPS while the A100 reaches 312 TFLOPS dense. This difference produces more than four times the throughput for training workloads that rely on dense FP16 operations. FP32 performance on the MI300X reaches 163.4 TFLOPS while the A100 reaches 19.5 TFLOPS. The MI300X therefore supplies more than eight times the throughput for workloads that rely on FP32 operations. Memory bandwidth on the MI300X reaches 5300 GB/s while the A100 reaches 2039 GB/s. Higher bandwidth supports larger batch sizes during both training and inference because data movement keeps pace with the higher 1307.4 TFLOPS dense FP16 rate.

The A100 suits deployments that require 400W TDP rather than 750W TDP. Its SXM4 and PCIe form factors along with NVLink interconnect support existing cluster designs that cannot accommodate OAM modules or Infinity Fabric. Workloads that fit within 80 GB HBM2e memory avoid the need for the higher 192 GB capacity of newer cards.

The MI300X suits workloads that require 192 GB HBM3 memory and 5300 GB/s bandwidth. Its 1307.4 TFLOPS FP16 dense rating and 163.4 TFLOPS FP32 rating accelerate large model training that exceeds the 80 GB limit of the A100. PCIe 5.0 interconnect matches newer server platforms that do not rely on NVLink.