Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 mini has the cleaner overall profile here, landing at 35 versus 33. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 75.9 against 27. The single biggest benchmark swing on the page is MMLU, 87.5 to 29. Mistral 8x7B v0.2 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 8x7B v0.2.
Pick GPT-4.1 mini if you want the stronger benchmark profile. Mistral 8x7B v0.2 only becomes the better choice if mathematics is the priority.
GPT-4.1 mini
75.9
Mistral 8x7B v0.2
27
GPT-4.1 mini
23.6
Mistral 8x7B v0.2
16.3
GPT-4.1 mini
23.1
Mistral 8x7B v0.2
31.9
GPT-4.1 mini
88.5
Mistral 8x7B v0.2
67
GPT-4.1 mini is ahead overall, 35 to 33. The biggest single separator in this matchup is MMLU, where the scores are 87.5 and 29.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 27. 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 16.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Mistral 8x7B v0.2 has the edge for math in this comparison, averaging 31.9 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 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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