GLM 5/5.1 — GB200 NVL72 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on GLM 5/5.1. 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.
On GLM 5/5.1 at 50 tok/s/user, the per-million math comes out to $0.33 for GB200 NVL72 and $0.28 for GB300 NVL72; GB300 NVL72 delivers 19% more output per dollar.
At 62 tok/s/user on GLM 5/5.1, GB200 NVL72 costs $0.47 per million tokens; GB300 NVL72 costs $0.65. GB200 NVL72 is 36% more cost-efficient at this operating point.
GB200 NVL72 edges GB300 NVL72 at 73 tok/s/user on GLM 5/5.1 — $1.09 per million tokens versus $1.52, a 40% cost-per-token gap. (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): GB200 NVL72 $2.21/GPU/hr · GB300 NVL72 $2.65/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 | GB200 NVL72:$0.334GB300 NVL72:$0.281 | GB200 NVL72:$0.474GB300 NVL72:$0.646 | GB200 NVL72:$1.089GB300 NVL72:$1.521 |
| Concurrency | GB200 NVL72:~142GB300 NVL72:~278 | GB200 NVL72:~130GB300 NVL72:~59 | GB200 NVL72:~109GB300 NVL72:~30 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.