Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o1 is clearly ahead on the aggregate, 51 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1's sharpest advantage is in knowledge, where it averages 83.8 against 71.2. The single biggest benchmark swing on the page is GPQA, 75.7 to 71.2. GPT-5 nano does hit back in mathematics, 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 $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. That is roughly 150.0x on output cost alone. GPT-5 nano gives you the larger context window at 400K, compared with 200K for o1.
Pick o1 if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
o1
83.8
GPT-5 nano
71.2
o1
74.3
GPT-5 nano
85.2
o1 is ahead overall, 51 to 31. The biggest single separator in this matchup is GPQA, where the scores are 75.7 and 71.2.
o1 has the edge for knowledge tasks in this comparison, averaging 83.8 versus 71.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 74.3. o1 stays close enough that the answer can still flip depending on your workload.
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