H200 vs Quadro P5000

The H200 lists FP32 performance at 67 TFLOPS while the Quadro P5000 lists FP32 performance at 8.9 TFLOPS. This gap indicates the H200 processes floating point operations at a higher rate during training and inference steps that rely on FP32 precision. The H200 also lists dense FP16 performance at 989 TFLOPS with no corresponding figure published for the Quadro P5000. Memory bandwidth differences of 4800 GB/s versus 288 GB/s allow the H200 to support larger batch sizes in memory intensive operations compared with the Quadro P5000. Dense FP16 figures on the H200 reach 989 TFLOPS while sparse FP16 figures reach 1979 TFLOPS. These values remain separate from the 67 TFLOPS dense FP32 rating and cannot be mixed in ratio calculations.

The H200 suits LLM training workloads that require 141 GB HBM3e capacity and 4800 GB/s bandwidth for large model handling. Organizations select the H200 when dense FP16 performance at 989 TFLOPS supports accelerated matrix operations beyond the 8.9 TFLOPS FP32 limit of older cards. The 700W TDP fits data center racks that accommodate higher power draw for sustained throughput.

The Quadro P5000 fits scientific computing tasks that operate within 16 GB GDDR5X limits and 180W TDP constraints. Legacy systems benefit from the PCIe 3.0 interconnect and 8.9 TFLOPS FP32 rating when power budgets prohibit 700W devices.