B200 vs RTX 2070

The FP16 dense figure of 2250 TFLOPS on the B200 exceeds the 29.9 TFLOPS dense FP16 rating of the RTX 2070 by a wide margin. This gap means the B200 completes training iterations and inference passes on large models in far less time than the RTX 2070 can achieve with its 7.5 TFLOPS FP32 rating. Memory bandwidth of 8000 GB/s on the B200 supports substantially larger batch sizes than the 448 GB/s available on the RTX 2070. FP16 dense performance on the B200 also surpasses the RTX 2070 when both are measured under dense conditions. The B200 further lists FP16 with sparsity at 4500 TFLOPS while the RTX 2070 provides no sparsity figure for that precision.

The B200 suits workloads that require 180 to 192 GB of memory and 2250 TFLOPS FP16 dense throughput. Organizations running large scale training or inference select the B200 because its 8000 GB/s bandwidth and 1000W TDP accommodate models that exceed the 8 GB limit of older cards. The B200 also supplies INT8 dense performance of 4500 TOPS for quantized inference pipelines.

The RTX 2070 fits environments where power draw must remain near 175W and memory needs stay below 8 GB. Legacy applications that rely on the Turing architecture and PCIe 3.0 interconnect continue to operate on the RTX 2070 without requiring the 1000W TDP of newer hardware. The RTX 2070 also supplies 119.4 TOPS INT8 dense for modest inference tasks.