Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 is clearly ahead on the aggregate, 43 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in knowledge, where it averages 78.3 against 71.2. The single biggest benchmark swing on the page is GPQA, 66.3 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.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. That is roughly 20.0x on output cost alone. GPT-5 nano is the reasoning model in the pair, while GPT-4.1 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 gives you the larger context window at 1M, compared with 400K for GPT-5 nano.
Pick GPT-4.1 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.
GPT-4.1
78.3
GPT-5 nano
71.2
GPT-4.1
26.4
GPT-5 nano
85.2
GPT-4.1 is ahead overall, 43 to 31. The biggest single separator in this matchup is GPQA, where the scores are 66.3 and 71.2.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 78.3 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 26.4. GPT-4.1 stays close enough that the answer can still flip depending on your workload.
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