
B300's cost-per-token math extends the same logic established across B200: the premium only pays off when it genuinely changes your setup, either by avoiding a multi-GPU split that even B200 would need, or by unlocking NVFP4 throughput gains once your engine supports it. For models that already run efficiently on B200, H200 or H100, B300 raises cost per token for identical work. B200, H200 and H100 cost per token cover the same batching, quantization and engine levers that apply equally to B300.
B300's cost-per-token calculation extends the same logic established across H100, H200 and B200: 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 B200, purely for memory reasons rather than compute demand; moving that model to a single B300 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 B200 or H200, B300 offers no corresponding benefit and simply raises cost per token for identical work. Native NVFP4 support represents real future upside once mainstream serving engines fully support it, but most B300 cost-per-token figures today still reflect FP8 or BF16 performance rather than NVFP4's full potential, the same adoption pattern B200's FP4 followed.
The hourly rate you pay for B300 capacity is one input into cost per token, and it varies meaningfully by region and provider. See B300 availability by country below.
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