Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 is clearly ahead on the aggregate, 43 to 34. 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 28.3. The single biggest benchmark swing on the page is MMLU, 90.2 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 gives you the larger context window at 1M, compared with 32K for Mistral 7B v0.3.
Pick GPT-4.1 if you want the stronger benchmark profile. Mistral 7B v0.3 only becomes the better choice if mathematics is the priority.
GPT-4.1
78.3
Mistral 7B v0.3
28.3
GPT-4.1
54.6
Mistral 7B v0.3
17
GPT-4.1
26.4
Mistral 7B v0.3
32.9
GPT-4.1
87.4
Mistral 7B v0.3
68
GPT-4.1 is ahead overall, 43 to 34. The biggest single separator in this matchup is MMLU, where the scores are 90.2 and 30.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 78.3 versus 28.3. 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 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 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 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.