Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Mistral Medium 3.5 delivers a 11% cost reduction over Gemini 3.5 Flash (OpenRouter).
| Traffic Volume Tier | Mistral Medium 3.5 Monthly | Gemini 3.5 Flash (OpenRouter) Monthly | Monthly Savings by picking Mistral Medium 3.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $23.28 | $26.28 | Save $3.00 / mo |
| 10,000 reqs/mo (Small App) | $232.80 | $262.80 | Save $30.00 / mo |
| 100,000 reqs/mo (Growth Production) | $2,328.00 | $2,628.00 | Save $300.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $23,280.00 | $26,280.00 | Save $3,000.00 / mo |
Mistral Medium 3.5 is 11% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Mistral Medium 3.5 costs $0.0233 per request compared to $0.0263 on Gemini 3.5 Flash (OpenRouter).
Mistral Medium 3.5 offers a context window of 256,000 tokens (max output: 32,768), while Gemini 3.5 Flash (OpenRouter) offers 1,048,576 tokens (max output: 65,536).
At 100,000 requests per month, using Mistral Medium 3.5 saves $300.00 every month (or $3,600.00 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.