A Comparison of AI Models: o4-mini vs. Gemini 2.5 Flash

In the rapidly evolving landscape of Artificial Intelligence, the competition among models continues to heat up. Recently, I put two popular contenders, o4-mini and Gemini 2.5 Flash, through their paces by testing them on 100 questions across various categories. The results reveal notable strengths and weaknesses for both, making this comparison essential for anyone interested in efficient AI solutions.

Summary of Findings

In a nutshell, both models demonstrated commendable performance and offer great value for their respective costs. However, Gemini 2.5 Flash has shown remarkable improvement, outpacing its predecessor, Gemini 2.5 Pro, in several metrics. Google appears to be making significant strides in refining their AI capabilities, and the results speak for themselves!

Detailed Performance Breakdown

| Test Category | o4-mini Score | Gemini 2.5 Flash Score | Winner / Comments |
|—————————————-|—————–|————————–|—————————————–|
| Pricing (Cost per M Tokens) | Input: $1.10
Output: $4.40
Total: $5.50 | Input: $0.15
Output: $3.50 (Reasoning)
Output: $0.60
Total: ~ $3.65 | Gemini 2.5 Flash is significantly more affordable. |
| Harmful Question Detection | 80.00 | 100.00 | Gemini 2.5 Flash excelled, while o4-mini struggled with recognizing ASCII camouflage and leetspeak. |
| Named Entity Recognition (New) | 90.00 | 95.00 | Gemini 2.5 Flash took a slight advantage, although both had minor errors; o4-mini faltered on a translation task, and Gemini missed some location details. |
| SQL Query Generator | 100.00 | 95.00 | o4-mini prevailed here, as Gemini produced an invalid SQL statement containing a syntax error. |
| Retrieval Augmented Generation | 100.00 | 100.00 | Tie – Both models handled challenging questions flawlessly. |

Conclusion

The test results illustrate that both o4-mini and Gemini 2.5 Flash hold up well under various