Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 31. 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 71.2. The single biggest benchmark swing on the page is GPQA, 77.2 to 71.2.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. That is roughly 11.0x on output cost alone. GPT-5 nano gives you the larger context window at 400K, compared with 200K for o3-mini.
Pick o3-mini if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if you want the cheaper token bill or you need the larger 400K context window.
o3-mini
82.1
GPT-5 nano
71.2
o3-mini
87.3
GPT-5 nano
85.2
o3-mini is ahead overall, 56 to 31. The biggest single separator in this matchup is GPQA, where the scores are 77.2 and 71.2.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 71.2. 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 85.2. GPT-5 nano stays close enough that the answer can still flip depending on your workload.
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