Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Flash-Lite is clearly ahead on the aggregate, 55 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Gemini 3.1 Flash-Lite. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 128K for GPT-4o mini.
Pick Gemini 3.1 Flash-Lite if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority.
Gemini 3.1 Flash-Lite
51.2
GPT-4o mini
82
Gemini 3.1 Flash-Lite
32.7
GPT-4o mini
87.2
Gemini 3.1 Flash-Lite
73
GPT-4o mini
87
Gemini 3.1 Flash-Lite is ahead overall, 55 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 55 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 51.2. 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 32.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 73. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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