GLM 5.3 744B — GB200 NVL72 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on GLM 5.3 744B. 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.
AgentX replays real coding-agent sessions rather than fixed-length prompts, so context grows turn over turn and most of each request is served from cache instead of being recomputed. That turns the comparison into a systems question: KV transfer between nodes, prefix-aware routing, and cache capacity all move the curve alongside raw chip throughput. Fixed-sequence workloads stay the clean baseline for kernel and silicon performance, so the two scenarios answer different questions about the same hardware. Learn more about AgentX →
At 143 tok/s/user on GLM 5.3 744B, GB200 NVL72 costs $0.04 per million tokens; GB300 NVL72 costs $0.05. GB200 NVL72 is 8% more cost-efficient at this operating point.
GB200 NVL72 edges GB300 NVL72 at 195 tok/s/user on GLM 5.3 744B — $0.06 per million tokens versus $0.07, a 13% cost-per-token gap.
Push GLM 5.3 744B to 246 tok/s/user and GB200 NVL72 lands at $0.10 per million tokens against GB300 NVL72's $0.11 — GB200 NVL72 pulls ahead by 2%. (Numbers reflect the default agentic-traces · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): GB200 NVL72 $1.86/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 | GB200 NVL72:$0.042GB300 NVL72:$0.045 | GB200 NVL72:$0.061GB300 NVL72:$0.069 | GB200 NVL72:$0.104GB300 NVL72:$0.106 |
| Concurrency | GB200 NVL72:~63GB300 NVL72:~56 | GB200 NVL72:~39GB300 NVL72:~21 | GB200 NVL72:~5GB300 NVL72:~16 |
Inference Performance
Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.