Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3 Flash is clearly ahead on the aggregate, 65 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Flash's sharpest advantage is in multilingual, where it averages 85 against 80.6. The single biggest benchmark swing on the page is HumanEval, 62 to 82.6. 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 Flash is also the more expensive model on tokens at $0.50 input / $3.00 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 Flash gives you the larger context window at 1M, compared with 16K for Phi-4.
Pick Gemini 3 Flash 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 Flash
58.2
Phi-4
70.5
Gemini 3 Flash
47.3
Phi-4
82.6
Gemini 3 Flash
85
Phi-4
80.6
Gemini 3 Flash is ahead overall, 65 to 39. The biggest single separator in this matchup is HumanEval, where the scores are 62 and 82.6.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 70.5 versus 58.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Phi-4 has the edge for coding in this comparison, averaging 82.6 versus 47.3. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Gemini 3 Flash has the edge for multilingual tasks in this comparison, averaging 85 versus 80.6. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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