A40 vs RTX 3090

The A40 delivers 149.7 TFLOPS in dense FP16 while the RTX 3090 delivers 71 TFLOPS in dense FP16. This gap means the A40 completes dense FP16 matrix operations more than twice as fast as the RTX 3090 during training or inference steps that rely on dense FP16. When sparsity is applied the A40 reaches 299.4 TFLOPS in FP16 with sparsity against 142 TFLOPS in FP16 with sparsity on the RTX 3090. The RTX 3090 higher memory bandwidth of 936 GB/s compared with 696 GB/s on the A40 can support larger batch sizes in bandwidth limited kernels despite the smaller 24 GB VRAM capacity. Dense INT8 performance stands at 299.3 TOPS on the A40 versus 284 TOPS on the RTX 3090.

The A40 suits workloads that require the full 48 GB VRAM capacity such as large model training or fine tuning sessions. Its 149.7 TFLOPS dense FP16 rating and 37.4 TFLOPS FP32 rating provide higher throughput than the RTX 3090 for precision sensitive scientific computing tasks. The lower 300 W TDP also reduces power draw relative to the 350 W TDP of the RTX 3090.

The RTX 3090 fits scenarios where the 936 GB/s memory bandwidth enables higher throughput in memory bound operations despite the 24 GB VRAM limit. Its 71 TFLOPS dense FP16 performance remains adequate for inference workloads that fit within the available memory. The 35.6 TFLOPS FP32 rating supports general purpose graphics tasks at a competitive level.