GLM 5.3 744B — B300 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on GLM 5.3 744B. Large-hyperscaler-volume ownership TCO normalized by total 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 →
GB300 NVL72 edges B300 at 148 tok/s/user on GLM 5.3 744B — $0.04 per million tokens versus $0.04, a 12% cost-per-token gap.
Push GLM 5.3 744B to 205 tok/s/user and B300 lands at $0.09 per million tokens against GB300 NVL72's $0.06 — GB300 NVL72 pulls ahead by 41%.
B300: $0.11 per million tokens. GB300 NVL72: $0.15. Both at 262 tok/s/user on GLM 5.3 744B, with B300 33% cheaper. (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): 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:$0.044GB300 NVL72:$0.040 | B300:$0.087GB300 NVL72:$0.061 | B300:$0.114GB300 NVL72:$0.152 |
| Concurrency | B300:~9GB300 NVL72:~55 | B300:~8GB300 NVL72:~20 | B300:~1GB300 NVL72:~4 |
Inference Performance
Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.
No data available
No measurements to plot for this selection. Review the benchmark controls above or adjust quick filters.