P100 vs Quadro RTX 4000

Dense FP16 throughput on the Quadro RTX 4000 reaches 57 TFLOPS compared with 18.7 TFLOPS dense FP16 on the P100. This difference favors the Quadro RTX 4000 for inference workloads that rely on dense FP16 operations. Training workloads that stay within 8 GB may also complete faster on the Quadro RTX 4000 because of the higher dense FP16 rating. Memory bandwidth of 732 GB/s on the P100 versus 416 GB/s on the Quadro RTX 4000 influences maximum batch size in memory bound kernels. Larger batches become feasible on the P100 when data movement dominates execution time. FP32 performance remains close with 9.3 TFLOPS on the P100 and 7.1 TFLOPS on the Quadro RTX 4000 so single precision scientific codes show smaller gaps than tensor workloads.

NVLink support further enables multi GPU scaling in clusters that already contain compatible hosts. Dense FP32 at 9.3 TFLOPS combined with 16 GB HBM2 memory supports large matrix operations without frequent host transfers.

The Quadro RTX 4000 suits inference pipelines that exploit 57 TFLOPS dense FP16 within an 8 GB footprint. TDP of 125W allows denser node configurations than the 250W P100. PCIe only connectivity matches standard workstation or cloud instances without NVLink requirements.