L40 vs RTX 2080

The L40 achieves FP16 dense performance of 181.05 TFLOPS while the RTX 2080 reaches 40.3 TFLOPS in the same dense FP16 metric. This difference means the L40 can process larger models or higher batch sizes during training and inference tasks that rely on dense FP16 calculations. The L40 also lists FP16 with sparsity at 362.1 TFLOPS but comparisons stay limited to dense against dense figures. Memory bandwidth of 864 GB/s on the L40 versus 448 GB/s on the RTX 2080 allows the L40 to sustain larger batch sizes without memory bottlenecks in data heavy operations. FP32 performance stands at 90.5 TFLOPS dense on the L40 against 10 TFLOPS on the RTX 2080 which affects precision sensitive scientific workloads. The L40 further specifies INT8 dense at 362 TOPS while the RTX 2080 lists INT8 dense at 161.1 TOPS.

The L40 suits workloads that require 48 GB GDDR6 VRAM and 864 GB/s memory bandwidth for handling large datasets. Its FP16 dense performance of 181.05 TFLOPS supports training and inference on bigger models than the RTX 2080 can manage with its 8 to 11 GB capacity. The 300W TDP remains acceptable when maximum throughput takes priority over power efficiency.

The RTX 2080 fits scenarios where 215W TDP reduces overall system power draw compared to the 300W TDP of the L40. Its 8 to 11 GB GDDR6 configuration works for smaller models that do not exceed this memory limit. The card also provides 40.3 TFLOPS dense FP16 and 10 TFLOPS FP32 for lighter inference or development tasks.