Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4o mini is clearly ahead on the aggregate, 43 to 39. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o mini's sharpest advantage is in knowledge, where it averages 82 against 70.5. The single biggest benchmark swing on the page is MGSM, 87 to 80.6.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 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. GPT-4o mini gives you the larger context window at 128K, compared with 16K for Phi-4.
Pick GPT-4o mini if you want the stronger benchmark profile. Phi-4 only becomes the better choice if you want the cheaper token bill.
GPT-4o mini
82
Phi-4
70.5
GPT-4o mini
87.2
Phi-4
82.6
GPT-4o mini
87
Phi-4
80.6
GPT-4o mini is ahead overall, 43 to 39. The biggest single separator in this matchup is MGSM, where the scores are 87 and 80.6.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 70.5. 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 82.6. 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 80.6. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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