RTX 5000 Ada vs V100

The RTX 5000 Ada delivers 65.3 TFLOPS in FP32 while the V100 delivers 15.7 TFLOPS in FP32. This fourfold difference in dense FP32 performance indicates the RTX 5000 Ada can complete matrix operations in scientific computing or inference pipelines in less time than the V100. The V100 provides 125 TFLOPS in dense FP16 which supports training workloads that fit within its published dense figure. Memory bandwidth of 900 GB/s on the V100 exceeds the 576 GB/s on the RTX 5000 Ada and therefore permits larger batch sizes in memory-bound kernels. The RTX 5000 Ada lists 1,044.4 TFLOPS in FP8 with sparsity which applies only to sparse workloads and cannot be compared directly to any dense figure from the V100. Lower TDP of 250W on the RTX 5000 Ada versus 300W on the V100 reduces power draw during extended runs.

The RTX 5000 Ada suits environments that require the 65.3 TFLOPS dense FP32 rating together with 32 GB VRAM and 250W TDP. PCIe 4.0 interconnect matches systems that lack NVLink support. Users select this card for inference tasks that benefit from the 1,044.4 TFLOPS FP8 with sparsity rating.

The V100 fits workloads that utilize the 125 TFLOPS dense FP16 rating and 900 GB/s memory bandwidth. NVLink interconnect supports multi-GPU scaling in training clusters. Systems that already contain V100 hardware continue to run dense FP16 jobs without migration.