Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Devstral 2 (2512) (OpenRouter) delivers a 97% cost reduction over o3-pro (Frontier Reasoning).
| Traffic Volume Tier | o3-pro (Frontier Reasoning) Monthly | Devstral 2 (2512) (OpenRouter) Monthly | Monthly Savings by picking Devstral 2 (2512) (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $270.40 | $6.829 | Save $263.571 / mo |
| 10,000 reqs/mo (Small App) | $2,704.00 | $68.288 | Save $2,635.712 / mo |
| 100,000 reqs/mo (Growth Production) | $27,040.00 | $682.88 | Save $26,357.12 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $270,400.00 | $6,828.80 | Save $263,571.20 / mo |
Devstral 2 (2512) (OpenRouter) is 97% 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 $0.2704 on o3-pro (Frontier Reasoning).
o3-pro (Frontier Reasoning) offers a context window of 1,000,000 tokens (max output: 128,000), 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 $26,357.12 every month (or $316,285.44 annually) compared to o3-pro (Frontier Reasoning).
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.