Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Pro is clearly ahead on the aggregate, 89 to 51. 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 coding, where it averages 79 against 41. The single biggest benchmark swing on the page is SWE-bench Verified, 75 to 41.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 3.1 Pro. That is roughly 12.0x on output cost alone. o1 is the reasoning model in the pair, while Gemini 3.1 Pro 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. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 200K for o1.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. o1 only becomes the better choice if you want the stronger reasoning-first profile.
Gemini 3.1 Pro
86
o1
83.8
Gemini 3.1 Pro
79
o1
41
Gemini 3.1 Pro
97.1
o1
74.3
Gemini 3.1 Pro
95
o1
92.2
Gemini 3.1 Pro is ahead overall, 89 to 51. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 75 and 41.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 86 versus 83.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for coding in this comparison, averaging 79 versus 41. Inside this category, SWE-bench Verified 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 74.3. 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 92.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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