B200 vs V100

The FP16 dense performance ratio shows the B200 at 2250 TFLOPS against the V100 at 125 TFLOPS which produces an 18 times difference that shortens training iteration times for matrix heavy operations. The same dense FP16 comparison applies to inference where larger batch sizes become feasible on the B200 because its 8000 GB/s bandwidth exceeds the V100 bandwidth of 900 GB/s by a factor of nearly nine. FP32 workloads follow a similar pattern with the B200 at 75 TFLOPS versus the V100 at 15.7 TFLOPS allowing faster single precision scientific kernels. Sparsity figures appear only for the B200 at 4500 TFLOPS FP16 with sparsity so comparisons remain limited to dense values between the two GPUs.

The B200 suits large scale LLM training sessions that require the 2250 TFLOPS FP16 dense rating and 180 to 192 GB VRAM capacity. Its 8000 GB/s bandwidth supports bigger batch sizes during fine tuning runs that exceed the limits of older cards. Workloads needing FP4 dense performance at 9000 TFLOPS also favor the B200 over prior generations.

The V100 fits environments constrained to 300W TDP and existing PCIe 3.0 infrastructure. Its 16 to 32 GB VRAM and 15.7 TFLOPS FP32 rating remain adequate for legacy scientific computing codes that do not demand newer interconnects. Smaller inference tasks that fit within the 900 GB/s bandwidth avoid the higher power draw of 1000W systems.