Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
92
GPT-5.5
91
Verified leaderboard positions: Gemini 3.1 Pro unranked · GPT-5.5 #3
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.5 only becomes the better choice if reasoning is the priority or you want the stronger reasoning-first profile.
Reasoning
+7.9 difference
Multimodal
+12.4 difference
Gemini 3.1 Pro
GPT-5.5
$2 / $12
$5 / $30
109 t/s
N/A
29.71s
N/A
1M
1M
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.5 only becomes the better choice if reasoning is the priority or you want the stronger reasoning-first profile.
Gemini 3.1 Pro finishes one point ahead on BenchLM's provisional leaderboard, 92 to 91. 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.
Gemini 3.1 Pro's sharpest advantage is in multimodal & grounded, where it averages 82.8 against 70.4. The single biggest benchmark swing on the page is ARC-AGI-2, 77.1% to 85%. GPT-5.5 does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $2.00 input / $12.00 output per 1M tokens for Gemini 3.1 Pro. That is roughly 2.5x on output cost alone. GPT-5.5 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 is ahead on BenchLM's provisional leaderboard, 92 to 91. The biggest single separator in this matchup is ARC-AGI-2, where the scores are 77.1% and 85%.
GPT-5.5 has the edge for reasoning in this comparison, averaging 85 versus 77.1. 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 82.8 versus 70.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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