Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4o mini is clearly ahead on the aggregate, 43 to 35. 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 coding, where it averages 87.2 against 23.6. The single biggest benchmark swing on the page is MMLU, 82 to 87.5.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini. That is roughly 2.7x on output cost alone. GPT-4.1 mini gives you the larger context window at 1M, compared with 128K for GPT-4o mini.
Pick GPT-4o mini if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window.
GPT-4o mini
82
GPT-4.1 mini
75.9
GPT-4o mini
87.2
GPT-4.1 mini
23.6
GPT-4o mini is ahead overall, 43 to 35. The biggest single separator in this matchup is MMLU, where the scores are 82 and 87.5.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 75.9. 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 23.6. GPT-4.1 mini stays close enough that the answer can still flip depending on your workload.
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