Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-VL-32B is clearly ahead on the aggregate, 38 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-VL-32B's sharpest advantage is in multimodal & grounded, where it averages 52.2 against 30.4. The single biggest benchmark swing on the page is MMMU-Pro, 58 to 25. Ministral 3 3B (Reasoning) does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Ministral 3 3B (Reasoning) is the reasoning model in the pair, while Qwen2.5-VL-32B 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. Ministral 3 3B (Reasoning) gives you the larger context window at 128K, compared with 32K for Qwen2.5-VL-32B.
Pick Qwen2.5-VL-32B if you want the stronger benchmark profile. Ministral 3 3B (Reasoning) only becomes the better choice if instruction following is the priority or you need the larger 128K context window.
Qwen2.5-VL-32B
33.5
Ministral 3 3B (Reasoning)
34
Qwen2.5-VL-32B
14.3
Ministral 3 3B (Reasoning)
7.2
Qwen2.5-VL-32B
52.2
Ministral 3 3B (Reasoning)
30.4
Qwen2.5-VL-32B
43.2
Ministral 3 3B (Reasoning)
35.3
Qwen2.5-VL-32B
34.7
Ministral 3 3B (Reasoning)
25.2
Qwen2.5-VL-32B
67
Ministral 3 3B (Reasoning)
68
Qwen2.5-VL-32B
60.4
Ministral 3 3B (Reasoning)
59.7
Qwen2.5-VL-32B
49.7
Ministral 3 3B (Reasoning)
40.9
Qwen2.5-VL-32B is ahead overall, 38 to 31. The biggest single separator in this matchup is MMMU-Pro, where the scores are 58 and 25.
Qwen2.5-VL-32B has the edge for knowledge tasks in this comparison, averaging 34.7 versus 25.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for coding in this comparison, averaging 14.3 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for math in this comparison, averaging 49.7 versus 40.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for reasoning in this comparison, averaging 43.2 versus 35.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Ministral 3 3B (Reasoning) has the edge for agentic tasks in this comparison, averaging 34 versus 33.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for multimodal and grounded tasks in this comparison, averaging 52.2 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Ministral 3 3B (Reasoning) has the edge for instruction following in this comparison, averaging 68 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for multilingual tasks in this comparison, averaging 60.4 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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