Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Pro is clearly ahead on the aggregate, 89 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in mathematics, where it averages 97.1 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 99 to 9.8.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 12.5x on output cost alone.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill.
Gemini 3.1 Pro
86
GPT-4.1 nano
65.2
Gemini 3.1 Pro
97.1
GPT-4.1 nano
9.8
Gemini 3.1 Pro
95
GPT-4.1 nano
83.2
Gemini 3.1 Pro is ahead overall, 89 to 23. The biggest single separator in this matchup is AIME 2024, where the scores are 99 and 9.8.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 86 versus 65.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for math in this comparison, averaging 97.1 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for instruction following in this comparison, averaging 95 versus 83.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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