B200's cost-per-token math follows the same logic established for H200: the higher hourly rate only pays off when it genuinely changes your setup, either by avoiding a multi-GPU split that even H200 would need, or by unlocking FP4 throughput gains once your engine supports it. For models that already run efficiently on H100 or H200, B200 raises cost per token for identical work. Full NVIDIA B200 specs are available on request. H200 and H100 cost per token cover the same batching, quantization and engine levers that apply equally to B200, and B300 extends the same total-setup-cost logic one generation further.
B200's cost-per-token calculation extends the same logic established moving from H100 to H200: a higher hourly rate only pays off when it genuinely changes the setup a model needs, not as a blanket upgrade. The clearest win is a model that needs a multi-GPU split on even H200, purely for memory reasons rather than compute demand; moving that model to a single B200 can lower total cost per token despite the higher per-GPU rate, since fewer GPUs are being paid for in total. For models that already run efficiently on a single H100 or H200, B200 offers no corresponding benefit and simply raises cost per token for identical work. Native FP4 support represents real future upside once mainstream serving engines fully support it, but most B200 cost-per-token figures today still reflect FP8 or BF16 performance rather than FP4's full potential.
The hourly rate you pay for B200 capacity is one input into cost per token, and it varies meaningfully by region and provider. See B200 availability by country below.
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