Kimi K2.5/K2.6/K2.7-Code 1T — H200 vs Jalapeño Performance per Dollar
Cost per million tokens of H200 (NVIDIA Hopper) versus Jalapeño (OpenAI Jalapeño) on Kimi K2.5/K2.6/K2.7-Code 1T. 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.
Only Jalapeño has cost data at 219 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T — $0.16 per million tokens. H200 is unmeasured at this target.
Jalapeño costs $0.49 per million tokens at 377 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T; we have no H200 benchmark data at this exact target.
At 536 tok/s/user on Kimi K2.5/K2.6/K2.7-Code 1T, Jalapeño comes in at $0.52 per million tokens. H200 hasn't been benchmarked at this operating point. (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.)
Chip pricing (owning hyperscaler): H200 $1.22/chip/hr · Jalapeño $1.27/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 | H200:—Jalapeño:$0.165 | H200:—Jalapeño:$0.487 | H200:—Jalapeño:$0.517 |
| Concurrency | H200:—Jalapeño:~41 | H200:—Jalapeño:~2 | H200:—Jalapeño:~1 |