Performance and Cost-Effectiveness Comparison of NVIDIA B200 and H200

On November 12, 2026, DEV Community's AI section published a comparison of the NVIDIA B200 and the H200 for large model workloads, concluding that the B200 is indeed the more powerful of the two GPUs. Per GPU, the B200 offers 1.28x the memory, 1.7x the memory bandwidth, and 2.27x the dense FP8 math, and it adds FP4 Tensor Cores that the H200 lacks. On pricing, the Nodus pricing page lists the B200 at $5.50/hr and the H200 SXM at $3.593/hr, meaning the B200 costs 1.53 times as much. The article's rule of thumb is that the B200 is the better buy whenever it completes a job more than 1.53 times faster than the H200, while the H200 remains the better buy when the GPU sits partly idle or when 141 GB of memory is all a model needs. It also notes that the B200's bandwidth advantage makes it more cost-effective under fully loaded inference, whereas the H200 suits scenarios where memory capacity, rather than raw speed, is the binding constraint. Because the piece relies on a single vendor pricing page, its cost-effectiveness verdict is tied to those rates rather than to a cross-provider comparison.