Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 51. 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 74.3. The single biggest benchmark swing on the page is AIME 2024, 87.3 to 74.3. o1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $1.10 input / $4.40 output per 1M tokens for o3-mini. That is roughly 13.6x on output cost alone.
Pick o3-mini if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority.
o3-mini
82.1
o1
83.8
o3-mini
49.3
o1
41
o3-mini
87.3
o1
74.3
o3-mini
93.9
o1
92.2
o3-mini is ahead overall, 56 to 51. The biggest single separator in this matchup is AIME 2024, where the scores are 87.3 and 74.3.
o1 has the edge for knowledge tasks in this comparison, averaging 83.8 versus 82.1. 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 41. 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 74.3. 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 92.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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