GLM 5.3 744B · Performance per Dollar

GLM 5.3 744B — B200 vs GB300 NVL72 Performance per Dollar

Cost per million tokens of B200 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on GLM 5.3 744B. Owning-hyperscaler 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

Near the low end of the 96–297 tok/s/user interactivity band — at 146 tok/s/user — B200 runs $0.06 per million tokens on GLM 5.3 744B while GB300 NVL72 runs $0.05. GB300 NVL72 is the cheaper choice by 26%.

On GLM 5.3 744B at 197 tok/s/user, the per-million math comes out to $0.07 for B200 and $0.07 for GB300 NVL72; B200 delivers 3% more total tokens per dollar.

At 247 tok/s/user on GLM 5.3 744B, B200 costs $0.11 per million tokens; GB300 NVL72 costs $0.10. GB300 NVL72 is 3% more cost-efficient at this operating point. (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): B200 $1.73/chip/hr · GB300 NVL72 $2.31/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.

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GLM 5.3 744B: B200 versus GB300 NVL72 cost per million tokens at matched interactivity levels
B200 versus GB300 NVL72 cost per million tokens for this comparison's canonical default workload. Lower cost indicates better performance per dollar.
Interpolated from real benchmark data. Edit target interactivity values below to compare at different operating points.
Metric
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Dollar per Million Tokens
B200:$0.058GB300 NVL72:$0.046
B200:$0.069GB300 NVL72:$0.072
B200:$0.108GB300 NVL72:$0.104
Concurrency
B200:~12GB300 NVL72:~58
B200:~8GB300 NVL72:~23
B200:~5GB300 NVL72:~15

Inference Performance

Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.

Configuration

No data available

No measurements to plot for this selection. Review the benchmark controls above or adjust quick filters.