Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 35. 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 mathematics, where it averages 87.3 against 23.1. The single biggest benchmark swing on the page is AIME 2024, 87.3 to 23.1.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 2.8x on output cost alone. o3-mini is the reasoning model in the pair, while GPT-4.1 mini 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 200K for o3-mini.
Pick o3-mini if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
o3-mini
82.1
GPT-4.1 mini
75.9
o3-mini
49.3
GPT-4.1 mini
23.6
o3-mini
87.3
GPT-4.1 mini
23.1
o3-mini
93.9
GPT-4.1 mini
88.5
o3-mini is ahead overall, 56 to 35. The biggest single separator in this matchup is AIME 2024, where the scores are 87.3 and 23.1.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 75.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 49.3 versus 23.6. 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 23.1. 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 88.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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