L40 vs RTX 4060

The L40 lists an FP16 dense rating of 181.05 TFLOPS and an FP16 rating with sparsity of 362.1 TFLOPS. The RTX 4060 does not publish an FP16 figure so direct FP16 comparison is omitted. The L40 FP32 rating of 90.5 TFLOPS stands six times higher than the 15.1 TFLOPS rating of the RTX 4060. Memory bandwidth on the L40 reaches 864 GB per second, more than three times the 272 GB per second available on the RTX 4060, which directly limits sustainable batch sizes during training or inference passes. The L40 also lists FP8 dense performance at 362 TFLOPS and FP8 performance with sparsity at 724 TFLOPS while the RTX 4060 lists only an FP8 rating with sparsity of 242 TFLOPS.

The L40 suits workloads that require 48 GB of GDDR6 memory and 864 GB per second bandwidth such as large model inference or scientific computing jobs that exceed 16 GB. Its FP32 rating of 90.5 TFLOPS and 300 W TDP support sustained throughput on memory heavy tasks where the RTX 4060 memory limit would force smaller batches or model partitioning.

The RTX 4060 suits compact inference or fine tuning jobs that fit inside 8 to 16 GB of GDDR6 memory and that benefit from its 115 W TDP. Its FP32 rating of 15.1 TFLOPS remains adequate for lighter Stable Diffusion sessions or edge scale LLM inference where power draw and physical size matter more than peak throughput.