A40 vs V100

The FP16 dense performance of the A40 at 149.7 TFLOPS exceeds the FP16 dense performance of the V100 at 125 TFLOPS while the FP32 performance of the A40 at 37.4 TFLOPS exceeds the FP32 performance of the V100 at 15.7 TFLOPS. This delta indicates that the A40 can process larger batches during training and inference steps that rely on dense FP16 operations compared to the V100. The A40 also lists INT8 dense performance at 299.3 TOPS and INT8 performance with sparsity at 598.6 TOPS. Memory bandwidth differences mean the V100 at 900 GB/s can support larger batch sizes in bandwidth constrained operations than the A40 at 696 GB/s. The A40 provides FP16 performance with sparsity at 299.4 TFLOPS while the V100 does not publish a sparsity figure for FP16.

The A40 suits workloads that require the 48 GB GDDR6 VRAM capacity for larger model states during fine tuning or inference. Its 149.7 TFLOPS dense FP16 performance supports higher throughput in compute heavy tasks compared to the V100. The A40 also supplies 299.3 TOPS in dense INT8 for quantized inference scenarios.

The V100 suits workloads that benefit from the 900 GB/s memory bandwidth for data movement intensive operations. Its support for both SXM2 and PCIe form factors allows deployment flexibility in certain server configurations. The V100 remains relevant for scientific computing tasks that align with its 15.7 TFLOPS FP32 performance.