Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Flash-Lite is clearly ahead on the aggregate, 55 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Flash-Lite's sharpest advantage is in mathematics, where it averages 63.1 against 23.1. The single biggest benchmark swing on the page is AIME 2024, 65 to 23.1. GPT-4.1 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 4.0x on output cost alone.
Pick Gemini 3.1 Flash-Lite if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority.
Gemini 3.1 Flash-Lite
51.2
GPT-4.1 mini
75.9
Gemini 3.1 Flash-Lite
32.7
GPT-4.1 mini
23.6
Gemini 3.1 Flash-Lite
63.1
GPT-4.1 mini
23.1
Gemini 3.1 Flash-Lite
79
GPT-4.1 mini
88.5
Gemini 3.1 Flash-Lite is ahead overall, 55 to 35. The biggest single separator in this matchup is AIME 2024, where the scores are 65 and 23.1.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 51.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Gemini 3.1 Flash-Lite has the edge for coding in this comparison, averaging 32.7 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Gemini 3.1 Flash-Lite has the edge for math in this comparison, averaging 63.1 versus 23.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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