L40 vs V100

Dense FP16 performance reaches 181.05 TFLOPS on the L40 compared with 125 TFLOPS on the V100. This gap means the L40 processes larger batches or deeper models in the same time when training or inference workloads rely on dense FP16 arithmetic. FP32 figures show the L40 at 90.5 TFLOPS against 15.7 TFLOPS on the V100 so single precision scientific kernels complete faster on the L40. Memory bandwidth of 864 GB/s on the L40 versus 900 GB/s on the V100 implies similar data movement rates yet the L40 pairs this with 48 GB capacity allowing larger resident datasets before swapping occurs. Sparse FP16 on the L40 reaches 362.1 TFLOPS while the V100 publishes no sparse figure so only dense to dense comparison applies.

The L40 suits workloads that require 48 GB VRAM and dense FP16 throughput of 181.05 TFLOPS. Inference pipelines handling large context windows or high resolution images benefit from the 48 GB capacity paired with FP8 dense performance of 362 TFLOPS. Training sessions that stay within dense arithmetic gain from the 90.5 TFLOPS FP32 rating and the 181.05 TFLOPS dense FP16 rating.

The V100 fits environments already equipped with NVLink interconnects and PCIe 3.0 slots. Workloads that operate comfortably within 32 GB HBM2 and need only the published 125 TFLOPS dense FP16 continue without hardware changes. Legacy clusters that depend on the Volta architecture maintain compatibility through the V100 form factors of SXM2 and PCIe.