Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3 Pro Deep Think is clearly ahead on the aggregate, 85 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Pro Deep Think's sharpest advantage is in multilingual, where it averages 92 against 87. The single biggest benchmark swing on the page is MMLU, 99 to 82. GPT-4o mini does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemini 3 Pro Deep Think is the reasoning model in the pair, while GPT-4o mini 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 Pro Deep Think gives you the larger context window at 2M, compared with 128K for GPT-4o mini.
Pick Gemini 3 Pro Deep Think if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemini 3 Pro Deep Think
82.8
GPT-4o mini
82
Gemini 3 Pro Deep Think
69
GPT-4o mini
87.2
Gemini 3 Pro Deep Think
92
GPT-4o mini
87
Gemini 3 Pro Deep Think is ahead overall, 85 to 43. The biggest single separator in this matchup is MMLU, where the scores are 99 and 82.
Gemini 3 Pro Deep Think has the edge for knowledge tasks in this comparison, averaging 82.8 versus 82. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 69. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Gemini 3 Pro Deep Think has the edge for multilingual tasks in this comparison, averaging 92 versus 87. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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