Quadro P4000 vs RTX 3090

The FP32 performance of 35.6 TFLOPS on the RTX 3090 exceeds the 5.3 TFLOPS on the Quadro P4000 by a factor derived directly from those values. For training and inference the dense FP16 rating of 71 TFLOPS on the RTX 3090 supports larger model computations than the FP32 baseline alone while the dense INT8 rating of 284 TOPS further accelerates quantized workloads. The memory bandwidth of 936 GB/s versus 243 GB/s permits proportionally larger batch sizes during both training and inference steps. Sparse FP16 performance of 142 TFLOPS on the RTX 3090 doubles the dense FP16 figure of 71 TFLOPS and the same doubling applies to the sparse INT8 figure of 568 TOPS relative to its dense counterpart of 284 TOPS.

The Quadro P4000 suits environments where power draw must remain at 105W and VRAM requirements stay within 8 GB. Its PCIe 3.0 interconnect fits legacy systems that lack support for newer interfaces. Workloads limited to FP32 at 5.3 TFLOPS benefit from the lower TDP without excess capacity.

The RTX 3090 fits tasks that require 24 GB of VRAM and memory bandwidth of 936 GB/s for larger batches. Its dense FP16 performance of 71 TFLOPS and dense FP32 performance of 35.6 TFLOPS accelerate modern training and inference relative to the Quadro P4000. NVLink support adds scaling options unavailable on the older card.