Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 is clearly ahead on the aggregate, 43 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in knowledge, where it averages 78.3 against 27. The single biggest benchmark swing on the page is MMLU, 90.2 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 gives you the larger context window at 1M, compared with 32K for Mistral 8x7B v0.2.
Pick GPT-4.1 if you want the stronger benchmark profile. Mistral 8x7B v0.2 only becomes the better choice if mathematics is the priority.
GPT-4.1
78.3
Mistral 8x7B v0.2
27
GPT-4.1
54.6
Mistral 8x7B v0.2
16.3
GPT-4.1
26.4
Mistral 8x7B v0.2
31.9
GPT-4.1
87.4
Mistral 8x7B v0.2
67
GPT-4.1 is ahead overall, 43 to 33. The biggest single separator in this matchup is MMLU, where the scores are 90.2 and 29.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 78.3 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 54.6 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 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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