Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Kimi K2.7 Code (OpenRouter) delivers a 54% cost reduction over Mistral Medium 3.5.
| Traffic Volume Tier | Mistral Medium 3.5 Monthly | Kimi K2.7 Code (OpenRouter) Monthly | Monthly Savings by picking Kimi K2.7 Code (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $38.625 | $17.59 | Save $21.035 / mo |
| 10,000 reqs/mo (Small App) | $386.25 | $175.90 | Save $210.35 / mo |
| 100,000 reqs/mo (Growth Production) | $3,862.50 | $1,759.00 | Save $2,103.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $38,625.00 | $17,590.00 | Save $21,035.00 / mo |
Kimi K2.7 Code (OpenRouter) is 54% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Kimi K2.7 Code (OpenRouter) costs $0.0176 per request compared to $0.0386 on Mistral Medium 3.5.
Mistral Medium 3.5 offers a context window of 256,000 tokens (max output: 32,768), while Kimi K2.7 Code (OpenRouter) offers 262,144 tokens (max output: 235,929).
At 100,000 requests per month, using Kimi K2.7 Code (OpenRouter) saves $2,103.50 every month (or $25,242.00 annually) compared to Mistral Medium 3.5.
Long-context models pay off here — compare price per 1M tokens at your true document size. Summarize once, store the result; don't re-summarize unchanged documents. For batch backfills, nightly jobs can use cache-friendly request ordering.