DeepSeek V4 Pro 1.6T — B300 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on DeepSeek V4 Pro 1.6T. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
Push DeepSeek V4 Pro 1.6T to 71 tok/s/user and B300 lands at $0.26 per million tokens against GB300 NVL72's $0.07 — GB300 NVL72 pulls ahead by 284%.
B300: $0.50 per million tokens. GB300 NVL72: $0.19. Both at 129 tok/s/user on DeepSeek V4 Pro 1.6T, with GB300 NVL72 169% cheaper.
Toward the upper edge of the 13–244 tok/s/user interactivity band — at 187 tok/s/user — B300 runs $1.19 per million tokens on DeepSeek V4 Pro 1.6T while GB300 NVL72 runs $1.25. B300 is the cheaper choice by 5%. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): B300 $2.26/chip/hr · GB300 NVL72 $2.31/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | B300:$0.259GB300 NVL72:$0.067 | B300:$0.502GB300 NVL72:$0.187 | B300:$1.186GB300 NVL72:$1.250 |
| Concurrency | B300:~23GB300 NVL72:~1113 | B300:~5GB300 NVL72:~291 | B300:~1GB300 NVL72:~13 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.