Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Qwen3 Coder Next (OpenRouter) delivers a 91% cost reduction over Kimi K2.6.
| Traffic Volume Tier | Kimi K2.6 Monthly | Qwen3 Coder Next (OpenRouter) Monthly | Monthly Savings by picking Qwen3 Coder Next (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $37.725 | $3.355 | Save $34.37 / mo |
| 10,000 reqs/mo (Small App) | $377.25 | $33.55 | Save $343.70 / mo |
| 100,000 reqs/mo (Growth Production) | $3,772.50 | $335.50 | Save $3,437.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $37,725.00 | $3,355.00 | Save $34,370.00 / mo |
Qwen3 Coder Next (OpenRouter) is 91% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Qwen3 Coder Next (OpenRouter) costs $0.003355 per request compared to $0.0377 on Kimi K2.6.
Kimi K2.6 offers a context window of 1,000,000 tokens (max output: 32,768), while Qwen3 Coder Next (OpenRouter) offers 262,144 tokens (max output: 235,929).
At 100,000 requests per month, using Qwen3 Coder Next (OpenRouter) saves $3,437.00 every month (or $41,244.00 annually) compared to Kimi K2.6.
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.