Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 84. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 71.9. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 72. Gemini 3.1 Pro does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 3.1 Pro. That is roughly 30.0x on output cost alone. GPT-5.2 Pro 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 400K for GPT-5.2 Pro.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Gemini 3.1 Pro only becomes the better choice if multilingual is the priority or you want the cheaper token bill.
GPT-5.2 Pro
85.9
Gemini 3.1 Pro
76.1
GPT-5.2 Pro
84.8
Gemini 3.1 Pro
71.9
GPT-5.2 Pro
96
Gemini 3.1 Pro
95
GPT-5.2 Pro
95.2
Gemini 3.1 Pro
92.7
GPT-5.2 Pro
81.5
Gemini 3.1 Pro
79.4
GPT-5.2 Pro
95
Gemini 3.1 Pro
95
GPT-5.2 Pro
93.4
Gemini 3.1 Pro
94.1
GPT-5.2 Pro
98.2
Gemini 3.1 Pro
96.8
GPT-5.2 Pro is ahead overall, 90 to 84. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 72.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 79.4. Inside this category, FrontierScience is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 71.9. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 96.8. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 92.7. Inside this category, BBH is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 76.1. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 95. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro and Gemini 3.1 Pro are effectively tied for instruction following here, both landing at 95 on average.
Gemini 3.1 Pro has the edge for multilingual tasks in this comparison, averaging 94.1 versus 93.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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