Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Devstral 2 (2512) (OpenRouter) delivers a 74% cost reduction over Gemini 3.5 Flash (OpenRouter).
| Traffic Volume Tier | Gemini 3.5 Flash (OpenRouter) Monthly | Devstral 2 (2512) (OpenRouter) Monthly | Monthly Savings by picking Devstral 2 (2512) (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $26.28 | $6.829 | Save $19.451 / mo |
| 10,000 reqs/mo (Small App) | $262.80 | $68.288 | Save $194.512 / mo |
| 100,000 reqs/mo (Growth Production) | $2,628.00 | $682.88 | Save $1,945.12 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $26,280.00 | $6,828.80 | Save $19,451.20 / mo |
Devstral 2 (2512) (OpenRouter) is 74% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Devstral 2 (2512) (OpenRouter) costs $0.006829 per request compared to $0.0263 on Gemini 3.5 Flash (OpenRouter).
Gemini 3.5 Flash (OpenRouter) offers a context window of 1,048,576 tokens (max output: 65,536), while Devstral 2 (2512) (OpenRouter) offers 262,144 tokens (max output: 209,715).
At 100,000 requests per month, using Devstral 2 (2512) (OpenRouter) saves $1,945.12 every month (or $23,341.44 annually) compared to Gemini 3.5 Flash (OpenRouter).
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.