Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 33. 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 79. The single biggest benchmark swing on the page is GPQA, 77.2 to 79.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $1.10 input / $4.40 output per 1M tokens for o3-mini. That is roughly 136.4x on output cost alone.
Pick o3-mini if you want the stronger benchmark profile. o1-pro only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
o3-mini
82.1
o1-pro
79
o3-mini
87.3
o1-pro
86
o3-mini is ahead overall, 56 to 33. The biggest single separator in this matchup is GPQA, where the scores are 77.2 and 79.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 79. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 86. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
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