Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4 Turbo is clearly ahead on the aggregate, 47 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4 Turbo's sharpest advantage is in reasoning, where it averages 61 against 30.1. The single biggest benchmark swing on the page is HumanEval, 52 to 15.
Pick GPT-4 Turbo if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-4 Turbo
44.7
Ministral 3 3B
22.9
GPT-4 Turbo
17.2
Ministral 3 3B
6.2
GPT-4 Turbo
55.3
Ministral 3 3B
30.4
GPT-4 Turbo
61
Ministral 3 3B
30.1
GPT-4 Turbo
41.1
Ministral 3 3B
24.5
GPT-4 Turbo
80
Ministral 3 3B
67
GPT-4 Turbo
68.5
Ministral 3 3B
59.7
GPT-4 Turbo
64.4
Ministral 3 3B
36
GPT-4 Turbo is ahead overall, 47 to 27. The biggest single separator in this matchup is HumanEval, where the scores are 52 and 15.
GPT-4 Turbo has the edge for knowledge tasks in this comparison, averaging 41.1 versus 24.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for coding in this comparison, averaging 17.2 versus 6.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for math in this comparison, averaging 64.4 versus 36. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for reasoning in this comparison, averaging 61 versus 30.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for agentic tasks in this comparison, averaging 44.7 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for multimodal and grounded tasks in this comparison, averaging 55.3 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for instruction following in this comparison, averaging 80 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-4 Turbo has the edge for multilingual tasks in this comparison, averaging 68.5 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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