Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2 (Thinking) is clearly ahead on the aggregate, 70 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.2 (Thinking)'s sharpest advantage is in agentic, where it averages 69.4 against 48.4. The single biggest benchmark swing on the page is SWE-bench Pro, 58 to 34.
DeepSeek V3.2 (Thinking) is the reasoning model in the pair, while Ministral 3 14B 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 DeepSeek V3.2 (Thinking) if you want the stronger benchmark profile. Ministral 3 14B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeek V3.2 (Thinking)
69.4
Ministral 3 14B
48.4
DeepSeek V3.2 (Thinking)
51.2
Ministral 3 14B
33
DeepSeek V3.2 (Thinking)
71
Ministral 3 14B
70.5
DeepSeek V3.2 (Thinking)
80.6
Ministral 3 14B
63.6
DeepSeek V3.2 (Thinking)
64.4
Ministral 3 14B
50.1
DeepSeek V3.2 (Thinking)
85
Ministral 3 14B
80
DeepSeek V3.2 (Thinking)
80.8
Ministral 3 14B
76.8
DeepSeek V3.2 (Thinking)
85.1
Ministral 3 14B
69.7
DeepSeek V3.2 (Thinking) is ahead overall, 70 to 55. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 58 and 34.
DeepSeek V3.2 (Thinking) has the edge for knowledge tasks in this comparison, averaging 64.4 versus 50.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for coding in this comparison, averaging 51.2 versus 33. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for math in this comparison, averaging 85.1 versus 69.7. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for reasoning in this comparison, averaging 80.6 versus 63.6. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for agentic tasks in this comparison, averaging 69.4 versus 48.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for multimodal and grounded tasks in this comparison, averaging 71 versus 70.5. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for instruction following in this comparison, averaging 85 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for multilingual tasks in this comparison, averaging 80.8 versus 76.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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