Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-72B is clearly ahead on the aggregate, 64 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-72B's sharpest advantage is in mathematics, where it averages 83.5 against 47.8. The single biggest benchmark swing on the page is MMLU, 83 to 30.
Ministral 3 8B (Reasoning) is the reasoning model in the pair, while Qwen2.5-72B 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 Qwen2.5-72B if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
Qwen2.5-72B
57.7
Ministral 3 8B (Reasoning)
38.5
Qwen2.5-72B
43.8
Ministral 3 8B (Reasoning)
15.2
Qwen2.5-72B
66.7
Ministral 3 8B (Reasoning)
33.4
Qwen2.5-72B
75.8
Ministral 3 8B (Reasoning)
42.1
Qwen2.5-72B
59.8
Ministral 3 8B (Reasoning)
30
Qwen2.5-72B
85
Ministral 3 8B (Reasoning)
70
Qwen2.5-72B
80.8
Ministral 3 8B (Reasoning)
61.7
Qwen2.5-72B
83.5
Ministral 3 8B (Reasoning)
47.8
Qwen2.5-72B is ahead overall, 64 to 36. The biggest single separator in this matchup is MMLU, where the scores are 83 and 30.
Qwen2.5-72B has the edge for knowledge tasks in this comparison, averaging 59.8 versus 30. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for coding in this comparison, averaging 43.8 versus 15.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for math in this comparison, averaging 83.5 versus 47.8. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for reasoning in this comparison, averaging 75.8 versus 42.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for agentic tasks in this comparison, averaging 57.7 versus 38.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for multimodal and grounded tasks in this comparison, averaging 66.7 versus 33.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for instruction following in this comparison, averaging 85 versus 70. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for multilingual tasks in this comparison, averaging 80.8 versus 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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