Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Pro is clearly ahead on the aggregate, 89 to 39. 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 knowledge, where it averages 86 against 70.5. The single biggest benchmark swing on the page is GPQA, 97 to 56.1. Phi-4 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Phi-4. That is roughly Infinityx on output cost alone. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 16K for Phi-4.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Phi-4 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Gemini 3.1 Pro
86
Phi-4
70.5
Gemini 3.1 Pro
79
Phi-4
82.6
Gemini 3.1 Pro
96
Phi-4
80.6
Gemini 3.1 Pro is ahead overall, 89 to 39. The biggest single separator in this matchup is GPQA, where the scores are 97 and 56.1.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 86 versus 70.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Phi-4 has the edge for coding in this comparison, averaging 82.6 versus 79. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for multilingual tasks in this comparison, averaging 96 versus 80.6. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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