Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4o is clearly ahead on the aggregate, 56 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o's sharpest advantage is in multimodal & grounded, where it averages 72.2 against 30.4. The single biggest benchmark swing on the page is MMMU-Pro, 74 to 25.
GPT-4o is also the more expensive model on tokens at $2.50 input / $10.00 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.
Pick GPT-4o if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if you want the cheaper token bill.
GPT-4o
51.2
Ministral 3 3B
22.9
GPT-4o
32.2
Ministral 3 3B
6.2
GPT-4o
72.2
Ministral 3 3B
30.4
GPT-4o
64.6
Ministral 3 3B
30.1
GPT-4o
47.4
Ministral 3 3B
24.5
GPT-4o
82
Ministral 3 3B
67
GPT-4o
75.5
Ministral 3 3B
59.7
GPT-4o
71.8
Ministral 3 3B
36
GPT-4o is ahead overall, 56 to 27. The biggest single separator in this matchup is MMMU-Pro, where the scores are 74 and 25.
GPT-4o has the edge for knowledge tasks in this comparison, averaging 47.4 versus 24.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4o has the edge for coding in this comparison, averaging 32.2 versus 6.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o has the edge for math in this comparison, averaging 71.8 versus 36. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-4o has the edge for reasoning in this comparison, averaging 64.6 versus 30.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-4o has the edge for agentic tasks in this comparison, averaging 51.2 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-4o has the edge for multimodal and grounded tasks in this comparison, averaging 72.2 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4o has the edge for instruction following in this comparison, averaging 82 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-4o has the edge for multilingual tasks in this comparison, averaging 75.5 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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