Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Mistral Large 2 is clearly ahead on the aggregate, 64 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini is the reasoning model in the pair, while Mistral Large 2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. o3-mini gives you the larger context window at 200K, compared with 128K for Mistral Large 2.
Pick Mistral Large 2 if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Mistral Large 2
58.7
o3-mini
82.1
Mistral Large 2
49
o3-mini
49.3
Mistral Large 2
68.9
o3-mini
87.3
Mistral Large 2
83
o3-mini
93.9
Mistral Large 2 is ahead overall, 64 to 56. The biggest single separator in this matchup is MMLU, where the scores are 68 and 86.9.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 58.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 49.3 versus 49. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 68.9. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 83. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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