Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Codestral 2508 (OpenRouter) delivers a 81% cost reduction over o3-mini.
| Traffic Volume Tier | o3-mini Monthly | Codestral 2508 (OpenRouter) Monthly | Monthly Savings by picking Codestral 2508 (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $18.04 | $3.456 | Save $14.584 / mo |
| 10,000 reqs/mo (Small App) | $180.40 | $34.56 | Save $145.84 / mo |
| 100,000 reqs/mo (Growth Production) | $1,804.00 | $345.60 | Save $1,458.40 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $18,040.00 | $3,456.00 | Save $14,584.00 / mo |
Codestral 2508 (OpenRouter) is 81% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Codestral 2508 (OpenRouter) costs $0.003456 per request compared to $0.018 on o3-mini.
o3-mini offers a context window of 200,000 tokens (max output: 100,000), while Codestral 2508 (OpenRouter) offers 256,000 tokens (max output: 204,800).
At 100,000 requests per month, using Codestral 2508 (OpenRouter) saves $1,458.40 every month (or $17,500.80 annually) compared to o3-mini.
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.