A30 vs Quadro RTX 5000

The dense FP16 rating of 165 TFLOPS on the A30 exceeds the dense FP16 rating of 89.2 TFLOPS on the Quadro RTX 5000. This gap translates into faster matrix operations during both training and inference when workloads stay within dense arithmetic. The FP32 rating of 10.3 TFLOPS on the A30 sits below the 11.2 TFLOPS rating on the Quadro RTX 5000 so single precision scientific kernels may favor the older card. Memory bandwidth of 933 GB/s on the A30 versus 448 GB/s on the Quadro RTX 5000 permits larger batch sizes before memory stalls occur in inference pipelines. The A30 TDP of 165W versus 230W on the Quadro RTX 5000 further reduces cooling demands when dense FP16 throughput at 165 TFLOPS drives the workload.

The A30 suits LLM inference and fine tuning because its 24 GB HBM2 capacity and 165 TFLOPS dense FP16 exceed the corresponding 16 GB and 89.2 TFLOPS figures on the Quadro RTX 5000. Its 165W TDP also permits higher rack density than the 230W TDP of the Quadro RTX 5000.

The Quadro RTX 5000 suits scientific computing workloads that rely on its 11.2 TFLOPS FP32 rating which exceeds the 10.3 TFLOPS rating of the A30. Its 2018 Turing architecture remains adequate when dense FP16 demand stays below 89.2 TFLOPS.