Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3 235B 2507 (Reasoning) is clearly ahead on the aggregate, 42 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3 235B 2507 (Reasoning)'s sharpest advantage is in agentic, where it averages 45.9 against 22.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 47 to 19. Ministral 3 3B does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
Qwen3 235B 2507 (Reasoning) is the reasoning model in the pair, while Ministral 3 3B 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 Qwen3 235B 2507 (Reasoning) if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if multilingual is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3 235B 2507 (Reasoning)
45.9
Ministral 3 3B
22.9
Qwen3 235B 2507 (Reasoning)
22.8
Ministral 3 3B
6.2
Qwen3 235B 2507 (Reasoning)
42.1
Ministral 3 3B
30.4
Qwen3 235B 2507 (Reasoning)
49
Ministral 3 3B
30.1
Qwen3 235B 2507 (Reasoning)
34.1
Ministral 3 3B
24.5
Qwen3 235B 2507 (Reasoning)
68
Ministral 3 3B
67
Qwen3 235B 2507 (Reasoning)
58.8
Ministral 3 3B
59.7
Qwen3 235B 2507 (Reasoning)
48.5
Ministral 3 3B
36
Qwen3 235B 2507 (Reasoning) is ahead overall, 42 to 27. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 47 and 19.
Qwen3 235B 2507 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 34.1 versus 24.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for coding in this comparison, averaging 22.8 versus 6.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for math in this comparison, averaging 48.5 versus 36. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for reasoning in this comparison, averaging 49 versus 30.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for agentic tasks in this comparison, averaging 45.9 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 42.1 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3 235B 2507 (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.
Ministral 3 3B has the edge for multilingual tasks in this comparison, averaging 59.7 versus 58.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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