Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Flash-Lite is clearly ahead on the aggregate, 55 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Flash-Lite is also the more expensive model on tokens at $0.10 input / $0.40 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 Flash-Lite gives you the larger context window at 1M, compared with 16K for Phi-4.
Pick Gemini 3.1 Flash-Lite 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 Flash-Lite
51.2
Phi-4
70.5
Gemini 3.1 Flash-Lite
32.7
Phi-4
82.6
Gemini 3.1 Flash-Lite
73
Phi-4
80.6
Gemini 3.1 Flash-Lite is ahead overall, 55 to 39. The biggest single separator in this matchup is HumanEval, where the scores are 55 and 82.6.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 70.5 versus 51.2. 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 32.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Phi-4 has the edge for multilingual tasks in this comparison, averaging 80.6 versus 73. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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