DeepSeek V4 Pro 1.6T — B200 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus GB200 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.
At 43 tok/s/user on DeepSeek V4 Pro 1.6T, B200 costs $0.18 per million tokens; GB200 NVL72 costs $0.26. B200 is 42% more cost-efficient at this operating point.
B200 edges GB200 NVL72 at 79 tok/s/user on DeepSeek V4 Pro 1.6T — $0.67 per million tokens versus $1.05, a 57% cost-per-token gap.
Push DeepSeek V4 Pro 1.6T to 116 tok/s/user and B200 lands at $1.04 per million tokens against GB200 NVL72's $3.37 — B200 pulls ahead by 225%. (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.)
GPU pricing (owning hyperscaler): B200 $1.95/GPU/hr · GB200 NVL72 $2.21/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | B200:$0.180GB200 NVL72:$0.257 | B200:$0.668GB200 NVL72:$1.051 | B200:$1.036GB200 NVL72:$3.368 |
| Concurrency | B200:~74GB200 NVL72:~125 | B200:~10GB200 NVL72:~47 | B200:~4GB200 NVL72:~7 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.