NVIDIA B200 vs NVIDIA H200
Specs, monthly cost in taka and the workloads each GPU suits, side by side.
Tensor figures are NVIDIA's published numbers with sparsity (dense is half). Source: B200, H200.
The short answer
Pick the NVIDIA B200 if: You train large LLMs or need the fastest inference available, with 180 GB per GPU — 70B in FP16 fits on one card.
Pick the NVIDIA H200 if: You need the H100's speed with 141 GB — 70B models at 8-bit with room for long context, bigger batches, or memory-heavy retrieval workloads.
The NVIDIA B200 costs about 19% more per hour than the NVIDIA H200. If your model fits comfortably on the cheaper GPU and you are not short of time, the cheaper one usually wins. Compare with your own model →
Common questions
Which is faster, the NVIDIA B200 or the NVIDIA H200?
On paper the NVIDIA B200 is faster: 4,500 TFLOPS vs 1,979 TFLOPS FP16 tensor (with sparsity). Real-world speed depends on your model, batch size and memory bandwidth.
Which one costs less?
The NVIDIA H200 is ৳1,390 per hour and the NVIDIA B200 is ৳1,652, about 19% more. For 40 hours that is ৳55,600 vs ৳66,080.
Which has more memory?
The NVIDIA B200 has 180 GB and the NVIDIA H200 has 141 GB. Roughly, the NVIDIA B200 fits 70B in FP16; the NVIDIA H200 fits 70B at 8-bit with room to spare, 70B in FP16 (tight).
Which should I choose for my project?
Choose the NVIDIA B200 if: You train large LLMs or need the fastest inference available, with 180 GB per GPU — 70B in FP16 fits on one card. Choose the NVIDIA H200 if: You need the H100's speed with 141 GB — 70B models at 8-bit with room for long context, bigger batches, or memory-heavy retrieval workloads.