Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
MiniMax M1 80k is clearly ahead on the aggregate, 37 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M1 80k's sharpest advantage is in mathematics, where it averages 37.8 against 9.8. The single biggest benchmark swing on the page is MMLU, 36 to 80.1. GPT-4.1 nano does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 nano gives you the larger context window at 1M, compared with 80K for MiniMax M1 80k.
Pick MiniMax M1 80k if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
MiniMax M1 80k
31.3
GPT-4.1 nano
65.2
MiniMax M1 80k
37.8
GPT-4.1 nano
9.8
MiniMax M1 80k
68
GPT-4.1 nano
83.2
MiniMax M1 80k is ahead overall, 37 to 23. The biggest single separator in this matchup is MMLU, where the scores are 36 and 80.1.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 31.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
MiniMax M1 80k has the edge for math in this comparison, averaging 37.8 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for instruction following in this comparison, averaging 83.2 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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