Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 mini finishes one point ahead overall, 35 to 34. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 75.9 against 28.3. The single biggest benchmark swing on the page is MMLU, 87.5 to 30. Mistral 7B v0.3 does hit back in mathematics, 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 32K for Mistral 7B v0.3.
Pick GPT-4.1 mini if you want the stronger benchmark profile. Mistral 7B v0.3 only becomes the better choice if mathematics is the priority.
GPT-4.1 mini
75.9
Mistral 7B v0.3
28.3
GPT-4.1 mini
23.6
Mistral 7B v0.3
17
GPT-4.1 mini
23.1
Mistral 7B v0.3
32.9
GPT-4.1 mini
88.5
Mistral 7B v0.3
68
GPT-4.1 mini is ahead overall, 35 to 34. The biggest single separator in this matchup is MMLU, where the scores are 87.5 and 30.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 28.3. 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 17. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 has the edge for math in this comparison, averaging 32.9 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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