Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in knowledge, where it averages 82.1 against 42.7. The single biggest benchmark swing on the page is MMLU, 86.9 to 50.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for Gemini 2.5 Flash. That is roughly 7.3x on output cost alone. o3-mini is the reasoning model in the pair, while Gemini 2.5 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 2.5 Flash gives you the larger context window at 1M, compared with 200K for o3-mini.
Pick o3-mini if you want the stronger benchmark profile. Gemini 2.5 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
o3-mini
82.1
Gemini 2.5 Flash
42.7
o3-mini
49.3
Gemini 2.5 Flash
27.7
o3-mini
87.3
Gemini 2.5 Flash
51.9
o3-mini
93.9
Gemini 2.5 Flash
79
o3-mini is ahead overall, 56 to 49. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 50.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 42.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 49.3 versus 27.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 51.9. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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