Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o3-mini is clearly ahead on the aggregate, 71 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in mathematics, where it averages 87.3 against 36. The single biggest benchmark swing on the page is MMLU, 86.9 to 24.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 3B. That is roughly Infinityx on output cost alone. o3-mini is the reasoning model in the pair, while Ministral 3 3B 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 Ministral 3 3B.
Pick o3-mini if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
o3-mini
66.6
Ministral 3 3B
22.9
o3-mini
55.6
Ministral 3 3B
6.2
o3-mini
74.4
Ministral 3 3B
30.4
o3-mini
81.1
Ministral 3 3B
30.1
o3-mini
70.8
Ministral 3 3B
24.5
o3-mini
93.9
Ministral 3 3B
67
o3-mini
73
Ministral 3 3B
59.7
o3-mini
87.3
Ministral 3 3B
36
o3-mini is ahead overall, 71 to 27. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 24.
o3-mini has the edge for knowledge tasks in this comparison, averaging 70.8 versus 24.5. 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 55.6 versus 6.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 36. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for reasoning in this comparison, averaging 81.1 versus 30.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o3-mini has the edge for agentic tasks in this comparison, averaging 66.6 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
o3-mini has the edge for multimodal and grounded tasks in this comparison, averaging 74.4 versus 30.4. Inside this category, MMMU-Pro 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 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
o3-mini has the edge for multilingual tasks in this comparison, averaging 73 versus 59.7. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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