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 36. 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 multimodal & grounded, where it averages 55.3 against 33.4. The single biggest benchmark swing on the page is GPQA, 60 to 29.
Ministral 3 8B (Reasoning) is the reasoning model in the pair, while GPT-4 Turbo 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.
Pick GPT-4 Turbo if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
GPT-4 Turbo
44.7
Ministral 3 8B (Reasoning)
38.5
GPT-4 Turbo
17.2
Ministral 3 8B (Reasoning)
15.2
GPT-4 Turbo
55.3
Ministral 3 8B (Reasoning)
33.4
GPT-4 Turbo
61
Ministral 3 8B (Reasoning)
42.1
GPT-4 Turbo
41.1
Ministral 3 8B (Reasoning)
30
GPT-4 Turbo
80
Ministral 3 8B (Reasoning)
70
GPT-4 Turbo
68.5
Ministral 3 8B (Reasoning)
61.7
GPT-4 Turbo
64.4
Ministral 3 8B (Reasoning)
47.8
GPT-4 Turbo is ahead overall, 47 to 36. The biggest single separator in this matchup is GPQA, where the scores are 60 and 29.
GPT-4 Turbo has the edge for knowledge tasks in this comparison, averaging 41.1 versus 30. 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 15.2. 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 47.8. 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 42.1. 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 38.5. Inside this category, BrowseComp 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 33.4. 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 70. 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 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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