MODEL COMPARISON
Gemini 2.5 Flash Lite
vs GPT-4.1 Mini.
These are the two candidates in Jevrouter’s initial Balanced routing pool. Compare their API costs and limits, then evaluate the answers on your own workload.
Current catalog comparison
| Attribute | Google: Gemini 2.5 Flash Lite | OpenAI: GPT-4.1 Mini |
|---|---|---|
| Input / 1M tokens | $0.1 | $0.4 |
| Output / 1M tokens | $0.4 | $1.6 |
| Context window | 1,048,576 tokens | 1,047,576 tokens |
| Maximum output | 65,535 tokens | 32,768 tokens |
| Provider declares tools | Yes | Yes |
| 10,000 example requests | $2.0000 | $8.0000 |
Example workload: 1,000 billable input tokens and 250 billable output tokens per request. Base rates only; reasoning, caching, provider overrides, fees and retries can change final usage. Updated from the provider catalog: 2026-09-22T09:51:50.338Z.
Change the assumptions in the calculator →Choose an acceptance check before comparing answers
For extraction, score exact fields and missing data. For code, run tests. For support replies, check factual correctness, policy adherence and whether the issue was resolved. A lower price per token does not imply a lower cost per successful task.
The initial policy maps everyday tasks toward Flash Lite and coding signals toward GPT-4.1 Mini, subject to confidence and access constraints. This is the current policy design, not a claim that one model always wins in those categories.
What we have actually measured
A ten-example English/Chinese connectivity check passed its simple matching tests for both fixed models. Total supplier cost was $0.000126 for Flash Lite and $0.0003412 for GPT-4.1 Mini. The Jev policy cost $0.000454186 including classification.
Those examples were small, the scoring was shallow and a matching answer could still be truncated. They do not establish production quality or show routing savings. Use the routing guide to design a held-out evaluation with your actual task mix.