Kimi K2.5/K2.6/K2.7-Code 1T — H200 vs Jalapeño
Head-to-head AI inference benchmark comparison of H200 (NVIDIA Hopper) and Jalapeño (OpenAI Jalapeño) on Kimi K2.5/K2.6/K2.7-Code 1T. Latency, throughput, and cost across LLM workloads. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
Jalapeño hits 2143 tok/s/chip for $0.16 per million tokens at 219 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T. No H200 data at this operating point.
Jalapeño: 724 tok/s/chip, $0.49 per million tokens at 377 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T. H200 is unmeasured here.
At 536 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, Jalapeño delivers 682 tok/s/chip at $0.52 per million tokens; H200 hasn't been benchmarked at this target. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | H200:—Jalapeño:2142.8 | H200:—Jalapeño:724.5 | H200:—Jalapeño:681.7 |
| Cost ($/M tok) | H200:—Jalapeño:$0.165 | H200:—Jalapeño:$0.487 | H200:—Jalapeño:$0.517 |
| tok/s/MW | H200:—Jalapeño:1904703 | H200:—Jalapeño:643970 | H200:—Jalapeño:605976 |
| Concurrency | H200:—Jalapeño:~41 | H200:—Jalapeño:~2 | H200:—Jalapeño:~1 |