L40S vs MI300X

Dense FP16 throughput stands at 362.05 TFLOPS on the L40S and 1307.4 TFLOPS on the MI300X. The MI300X therefore supplies 3.6 times the dense FP16 operations per second. The same ratio appears when both GPUs run FP16 with sparsity at 733 TFLOPS versus 2614.9 TFLOPS. Training runs that fit within the 48 GB limit finish faster on the MI300X because its higher dense FP16 rating reduces iteration time. Memory bandwidth of 5300 GB/s on the MI300X versus 864 GB/s on the L40S permits batch sizes roughly six times larger before activation memory overflows. Inference workloads benefit similarly when models exceed 48 GB because the MI300X keeps entire layers resident. FP32 performance at 163.4 TFLOPS on the MI300X versus 91.6 TFLOPS on the L40S further widens the gap for mixed precision scientific kernels that rely on full precision accumulation.

The L40S fits deployments that must stay inside a 350W power envelope because its TDP is less than half the MI300X rating. PCIe form factor cards also integrate directly into existing server chassis without OAM trays. Workloads that remain under 48 GB therefore complete at lower facility power cost on the L40S.

The MI300X handles models that require 192 GB capacity because its memory is four times larger than the L40S. Bandwidth at 5300 GB/s supports batch sizes unattainable on the 864 GB/s L40S. Large scale training and inference therefore default to the MI300X when model size exceeds the smaller card limit.