GLM 5.3 744B · Performance per Dollar

GLM 5.3 744B — B300 vs GB200 NVL72 Performance per Dollar

Cost per million tokens of B300 (NVIDIA Blackwell) versus GB200 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

Near the low end of the 126–298 tok/s/user interactivity band — at 169 tok/s/user — B300 runs $0.08 per million tokens on GLM 5.3 744B while GB200 NVL72 runs $0.05. GB200 NVL72 is the cheaper choice by 71%.

On GLM 5.3 744B at 212 tok/s/user, the per-million math comes out to $0.12 for B300 and $0.08 for GB200 NVL72; GB200 NVL72 delivers 51% more output per dollar.

At 255 tok/s/user on GLM 5.3 744B, B300 costs $0.15 per million tokens; GB200 NVL72 costs $0.11. GB200 NVL72 is 35% 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): B300 $2.26/chip/hr · GB200 NVL72 $1.86/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.

View full latency + throughput comparison →

GLM 5.3 744B: B300 versus GB200 NVL72 cost per million tokens at matched interactivity levels
B300 versus GB200 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
B300:$0.084GB200 NVL72:$0.049
B300:$0.118GB200 NVL72:$0.078
B300:$0.149GB200 NVL72:$0.110
Concurrency
B300:~9GB200 NVL72:~48
B300:~6GB200 NVL72:~7
B300:~4GB200 NVL72:~5

Inference Performance

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