B200 vs RTX 2060

The B200 specification lists 2250 TFLOPS dense FP16 performance and 4500 TFLOPS with sparsity while the RTX 2060 lists no FP16 figure from the vendor. This dense FP16 delta indicates the B200 can execute matrix operations at rates 2250 TFLOPS above any comparable published RTX 2060 value for training workloads that rely on dense FP16. The B200 also lists 75 TFLOPS FP32 performance against 6.5 TFLOPS on the RTX 2060 so FP32 training steps complete at a ratio of 75 to 6.5. Memory bandwidth of 8000 GB/s on the B200 versus 336 GB/s on the RTX 2060 permits larger batch sizes during inference because data movement scales directly with the 8000 to 336 ratio. The B200 TDP of 1000W versus 160W on the RTX 2060 further constrains deployment density when dense FP8 performance of 4500 TFLOPS is required.

The B200 suits LLM training tasks that require 180 to 192 GB HBM3e memory and 2250 TFLOPS dense FP16 throughput. Workloads that scale with 8000 GB/s bandwidth and NVLink interconnect also favor the B200 over alternatives limited to 336 GB/s and PCIe 3.0.

The RTX 2060 fits scientific computing tasks that operate within 6.5 TFLOPS FP32 and 160W TDP constraints. Deployments that require only PCIe 3.0 form factor and 6 to 12 GB GDDR6 memory select the RTX 2060 when higher TDP and bandwidth figures are unnecessary.