Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Kimi K2.7 Code (OpenRouter) delivers a 58% cost reduction over Amazon Nova Premier.
| Traffic Volume Tier | Amazon Nova Premier Monthly | Kimi K2.7 Code (OpenRouter) Monthly | Monthly Savings by picking Kimi K2.7 Code (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $27.04 | $11.384 | Save $15.656 / mo |
| 10,000 reqs/mo (Small App) | $270.40 | $113.84 | Save $156.56 / mo |
| 100,000 reqs/mo (Growth Production) | $2,704.00 | $1,138.40 | Save $1,565.60 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $27,040.00 | $11,384.00 | Save $15,656.00 / mo |
Kimi K2.7 Code (OpenRouter) is 58% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Kimi K2.7 Code (OpenRouter) costs $0.0114 per request compared to $0.027 on Amazon Nova Premier.
Amazon Nova Premier offers a context window of 1,000,000 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 $1,565.60 every month (or $18,787.20 annually) compared to Amazon Nova Premier.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.