Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
93
GPT-5.2
83
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.2 only becomes the better choice if you want the stronger reasoning-first profile.
Reasoning
+24.2 difference
Multimodal
+4.4 difference
Gemini 3.1 Pro
GPT-5.2
$1.25 / $5
$2 / $8
109 t/s
73 t/s
29.71s
130.34s
1M
400K
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.2 only becomes the better choice if you want the stronger reasoning-first profile.
Gemini 3.1 Pro is clearly ahead on the provisional aggregate, 93 to 83. 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 reasoning, where it averages 77.1 against 52.9. The single biggest benchmark swing on the page is ARC-AGI-2, 77.1% to 52.9%.
GPT-5.2 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 3.1 Pro. GPT-5.2 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.
Gemini 3.1 Pro is ahead on BenchLM's provisional leaderboard, 93 to 83. The biggest single separator in this matchup is ARC-AGI-2, where the scores are 77.1% and 52.9%.
Gemini 3.1 Pro has the edge for reasoning in this comparison, averaging 77.1 versus 52.9. Inside this category, ARC-AGI-2 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 83.9 versus 79.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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