Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Instant finishes one point ahead overall, 85 to 84. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.2 Instant's sharpest advantage is in coding, where it averages 75.5 against 71.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 83 to 77. Gemini 3.1 Pro does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 Instant is also the more expensive model on tokens at $1.50 input / $6.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 3.1 Pro. GPT-5.2 Instant 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 128K for GPT-5.2 Instant.
Pick GPT-5.2 Instant if you want the stronger benchmark profile. Gemini 3.1 Pro only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
GPT-5.2 Instant
79.6
Gemini 3.1 Pro
76.1
GPT-5.2 Instant
75.5
Gemini 3.1 Pro
71.9
GPT-5.2 Instant
93.1
Gemini 3.1 Pro
95
GPT-5.2 Instant
90.9
Gemini 3.1 Pro
92.7
GPT-5.2 Instant
79.8
Gemini 3.1 Pro
79.4
GPT-5.2 Instant
95
Gemini 3.1 Pro
95
GPT-5.2 Instant
94.4
Gemini 3.1 Pro
94.1
GPT-5.2 Instant
97.2
Gemini 3.1 Pro
96.8
GPT-5.2 Instant is ahead overall, 85 to 84. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 83 and 77.
GPT-5.2 Instant has the edge for knowledge tasks in this comparison, averaging 79.8 versus 79.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for coding in this comparison, averaging 75.5 versus 71.9. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for math in this comparison, averaging 97.2 versus 96.8. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for reasoning in this comparison, averaging 92.7 versus 90.9. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for agentic tasks in this comparison, averaging 79.6 versus 76.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 93.1. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant and Gemini 3.1 Pro are effectively tied for instruction following here, both landing at 95 on average.
GPT-5.2 Instant has the edge for multilingual tasks in this comparison, averaging 94.4 versus 94.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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