B200 vs MI250X

The FP16 dense figure of 2250 TFLOPS on the B200 exceeds the FP16 dense figure of 383 TFLOPS on the MI250X by a ratio of 2250 to 383. This gap indicates the B200 can process larger batch sizes during training or inference steps that rely on dense FP16 operations. The FP32 performance of 75 TFLOPS on the B200 compared with 47.9 TFLOPS on the MI250X produces a similar advantage for precision sensitive scientific workloads. Memory bandwidth of 8000 GB/s on the B200 versus 3277 GB/s on the MI250X allows the B200 to sustain higher data movement rates between compute units and memory. The B200 also lists FP8 dense performance at 4500 TFLOPS while the MI250X does not publish an FP8 figure. Sparsity modes on the B200 reach 4500 TFLOPS for FP16 with sparsity and 9000 TFLOPS for FP8 with sparsity whereas the MI250X provides only dense figures.

The B200 suits LLM training tasks that require 2250 TFLOPS FP16 dense throughput and 180 to 192 GB memory capacity. Organizations running inference at FP4 dense rates of 9000 TFLOPS select the B200 because the MI250X lacks equivalent published tensor performance at that precision.

The MI250X fits deployments where TDP must stay at 560W and workloads operate within 128 GB memory limits. Scientific computing jobs that rely on 47.9 TFLOPS FP32 performance can use the MI250X when power budgets exclude the 1000W TDP of the B200.