Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Gemini 2.0 Flash delivers a 41% cost reduction over GPT-4o mini.
| Traffic Volume Tier | Gemini 2.0 Flash Monthly | GPT-4o mini Monthly | Monthly Savings by picking Gemini 2.0 Flash |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $1.46 | $2.46 | Save $1.00 / mo |
| 10,000 reqs/mo (Small App) | $14.60 | $24.60 | Save $10.00 / mo |
| 100,000 reqs/mo (Growth Production) | $146.00 | $246.00 | Save $100.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $1,460.00 | $2,460.00 | Save $1,000.00 / mo |
Gemini 2.0 Flash is 41% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Gemini 2.0 Flash costs $0.00146 per request compared to $0.00246 on GPT-4o mini.
Gemini 2.0 Flash offers a context window of 1,048,576 tokens (max output: 8,192), while GPT-4o mini offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using Gemini 2.0 Flash saves $100.00 every month (or $1,200.00 annually) compared to GPT-4o 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.