Muse Spark Open 816B — B300 vs GB200 NVL72 Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) versus GB200 NVL72 (NVIDIA Blackwell) on Muse Spark Open 816B. 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 →
GB200 NVL72 edges B300 at 123 tok/s/user on Muse Spark Open 816B — $0.03 per million tokens versus $0.03, a 9% cost-per-token gap.
Push Muse Spark Open 816B to 189 tok/s/user and B300 lands at $0.05 per million tokens against GB200 NVL72's $0.06 — B300 pulls ahead by 21%.
B300: $0.10 per million tokens. GB200 NVL72: $0.09. Both at 255 tok/s/user on Muse Spark Open 816B, with GB200 NVL72 15% 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 · GB200 NVL72 $1.86/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:$0.031GB200 NVL72:$0.028 | B300:$0.048GB200 NVL72:$0.058 | B300:$0.104GB200 NVL72:$0.091 |
| Concurrency | B300:~15GB200 NVL72:~13 | B300:~10GB200 NVL72:~7 | B300:~4GB200 NVL72:~3 |
Inference Performance
Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.
No data available
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