B200 vs RTX 5060

The B200 records FP32 throughput at 75 TFLOPS while the RTX 5060 records FP32 throughput at 19.2 TFLOPS. This gap indicates that the B200 sustains substantially larger model states during both training and inference passes. Memory bandwidth of 8000 GB/s on the B200 versus 448 GB/s on the RTX 5060 permits batch sizes on the B200 that exceed those feasible on the RTX 5060 by a factor derived directly from the bandwidth ratio. The B200 lists FP16 dense performance at 2250 TFLOPS and FP16 performance with sparsity at 4500 TFLOPS whereas the RTX 5060 provides no published FP16 figures. In FP4 the B200 lists dense performance at 9000 TFLOPS and performance with sparsity at 18000 TFLOPS while the RTX 5060 lists performance with sparsity at 614 TFLOPS. These labeled figures demonstrate that the B200 maintains higher throughput whether measured in dense or sparse modes for the published precisions.

The B200 suits workloads that require 180 GB to 192 GB of HBM3e memory and 8000 GB/s bandwidth to accommodate models that exceed the 8 GB to 16 GB capacity of the RTX 5060. Its 75 TFLOPS FP32 rating and 2250 TFLOPS FP16 dense rating further support sustained execution of large training or inference jobs that the 19.2 TFLOPS FP32 rating of the RTX 5060 cannot match at equivalent scale.

The RTX 5060 suits workloads that operate within 8 GB to 16 GB of GDDR7 memory and maintain power draw near the 145W TDP. Its PCIe form factor and 19.2 TFLOPS FP32 rating align with desktop inference or fine tuning tasks where the 1000W TDP and SXM form factor of the B200 exceed local infrastructure limits.