Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
MiniMax M1 80k has the cleaner overall profile here, landing at 37 versus 35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MiniMax M1 80k's sharpest advantage is in mathematics, where it averages 37.8 against 23.1. The single biggest benchmark swing on the page is MMLU, 36 to 87.5. 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 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 mini 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 mini
75.9
MiniMax M1 80k
18
GPT-4.1 mini
23.6
MiniMax M1 80k
37.8
GPT-4.1 mini
23.1
MiniMax M1 80k
68
GPT-4.1 mini
88.5
MiniMax M1 80k is ahead overall, 37 to 35. The biggest single separator in this matchup is MMLU, where the scores are 36 and 87.5.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 31.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for coding in this comparison, averaging 23.6 versus 18. Inside this category, SWE-bench Verified 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 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 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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