Head-to-head AI inference benchmark comparison of H200 (NVIDIA Hopper) and Vera Rubin NVL72 (NVIDIA Vera Rubin) on Qwen 3.8 Flash Next 176B-A6B. Latency, throughput, and cost across LLM workloads. Use the chart controls below to switch sequences, precisions, and metrics β 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 β
At 96 tok/s/user on Qwen 3.8 Flash Next 176B-A6B, H200 delivers 25435 tok/s/chip at $0.01 per million tokens; Vera Rubin NVL72 hasn't been benchmarked at this target.
H200 hits 15021 tok/s/chip for $0.02 per million tokens at 141 tok/s/user on Qwen 3.8 Flash Next 176B-A6B. No Vera Rubin NVL72 data at this operating point.
H200: 7509 tok/s/chip, $0.05 per million tokens at 186 tok/s/user on Qwen 3.8 Flash Next 176B-A6B. Vera Rubin NVL72 is unmeasured here. (Numbers reflect the default agentic-traces Β· fp8 selection for this URL β table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | H200:25435.1Vera Rubin NVL72:β | H200:15021.2Vera Rubin NVL72:β | H200:7509.1Vera Rubin NVL72:β |
| Cost ($/M tok) | H200:$0.013Vera Rubin NVL72:β | H200:$0.023Vera Rubin NVL72:β | H200:$0.045Vera Rubin NVL72:β |
| tok/s/MW | H200:18565741Vera Rubin NVL72:β | H200:10964369Vera Rubin NVL72:β | H200:5481100Vera Rubin NVL72:β |
| Concurrency | H200:~11Vera Rubin NVL72:β | H200:~8Vera Rubin NVL72:β | H200:~2Vera Rubin NVL72:β |
Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.
No measurements to plot for this selection. Review the benchmark controls above or adjust quick filters.
