Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek LLM 2.0 has the cleaner overall profile here, landing at 62 versus 60. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek LLM 2.0's sharpest advantage is in coding, where it averages 42.9 against 35. The single biggest benchmark swing on the page is HumanEval, 73 to 62. Ministral 3 14B (Reasoning) does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Ministral 3 14B (Reasoning) is the reasoning model in the pair, while DeepSeek LLM 2.0 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 LLM 2.0 if you want the stronger benchmark profile. Ministral 3 14B (Reasoning) only becomes the better choice if multimodal & grounded is the priority or you want the stronger reasoning-first profile.
DeepSeek LLM 2.0
57.9
Ministral 3 14B (Reasoning)
58.5
DeepSeek LLM 2.0
42.9
Ministral 3 14B (Reasoning)
35
DeepSeek LLM 2.0
64.5
Ministral 3 14B (Reasoning)
71.5
DeepSeek LLM 2.0
73.6
Ministral 3 14B (Reasoning)
69.2
DeepSeek LLM 2.0
57.5
Ministral 3 14B (Reasoning)
52.1
DeepSeek LLM 2.0
85
Ministral 3 14B (Reasoning)
81
DeepSeek LLM 2.0
78.8
Ministral 3 14B (Reasoning)
77.8
DeepSeek LLM 2.0
80.8
Ministral 3 14B (Reasoning)
75.2
DeepSeek LLM 2.0 is ahead overall, 62 to 60. The biggest single separator in this matchup is HumanEval, where the scores are 73 and 62.
DeepSeek LLM 2.0 has the edge for knowledge tasks in this comparison, averaging 57.5 versus 52.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for coding in this comparison, averaging 42.9 versus 35. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for math in this comparison, averaging 80.8 versus 75.2. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for reasoning in this comparison, averaging 73.6 versus 69.2. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for agentic tasks in this comparison, averaging 58.5 versus 57.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 71.5 versus 64.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for instruction following in this comparison, averaging 85 versus 81. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for multilingual tasks in this comparison, averaging 78.8 versus 77.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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