Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Ministral 3 14B is clearly ahead on the aggregate, 55 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ministral 3 14B's sharpest advantage is in multilingual, where it averages 76.8 against 52. The single biggest benchmark swing on the page is MMLU-ProX, 75 to 52. o1-pro does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 14B. That is roughly Infinityx on output cost alone. o1-pro is the reasoning model in the pair, while Ministral 3 14B 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-pro gives you the larger context window at 200K, compared with 128K for Ministral 3 14B.
Pick Ministral 3 14B if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Ministral 3 14B
48.4
o1-pro
39.7
Ministral 3 14B
33
o1-pro
23
Ministral 3 14B
70.5
o1-pro
48.5
Ministral 3 14B
63.6
o1-pro
56.2
Ministral 3 14B
50.1
o1-pro
69.9
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Ministral 3 14B
76.8
o1-pro
52
Ministral 3 14B
69.7
o1-pro
86
Ministral 3 14B is ahead overall, 55 to 45. The biggest single separator in this matchup is MMLU-ProX, where the scores are 75 and 52.
o1-pro has the edge for knowledge tasks in this comparison, averaging 69.9 versus 50.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for coding in this comparison, averaging 33 versus 23. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1-pro has the edge for math in this comparison, averaging 86 versus 69.7. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for reasoning in this comparison, averaging 63.6 versus 56.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for agentic tasks in this comparison, averaging 48.4 versus 39.7. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for multimodal and grounded tasks in this comparison, averaging 70.5 versus 48.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for multilingual tasks in this comparison, averaging 76.8 versus 52. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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