Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Mistral 8x7B is clearly ahead on the aggregate, 57 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1 is the reasoning model in the pair, while Mistral 8x7B 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. o1 gives you the larger context window at 200K, compared with 32K for Mistral 8x7B.
Pick Mistral 8x7B if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Mistral 8x7B
54
o1
83.8
Mistral 8x7B
35.3
o1
41
Mistral 8x7B
65.1
o1
74.3
Mistral 8x7B
78
o1
92.2
Mistral 8x7B is ahead overall, 57 to 51. The biggest single separator in this matchup is MMLU, where the scores are 65 and 91.8.
o1 has the edge for knowledge tasks in this comparison, averaging 83.8 versus 54. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 41 versus 35.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o1 has the edge for math in this comparison, averaging 74.3 versus 65.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 78. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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