Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Phi-4 is clearly ahead on the aggregate, 42 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Phi-4's sharpest advantage is in coding, where it averages 55 against 7.2. The single biggest benchmark swing on the page is HumanEval, 82.6 to 16. Ministral 3 3B (Reasoning) does hit back in reasoning, 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 Phi-4 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 16K for Phi-4.
Pick Phi-4 if you want the stronger benchmark profile. Ministral 3 3B (Reasoning) only becomes the better choice if reasoning is the priority or you need the larger 128K context window.
Phi-4
38.3
Ministral 3 3B (Reasoning)
34
Phi-4
55
Ministral 3 3B (Reasoning)
7.2
Phi-4
46.8
Ministral 3 3B (Reasoning)
30.4
Phi-4
31.3
Ministral 3 3B (Reasoning)
35.3
Phi-4
53.8
Ministral 3 3B (Reasoning)
25.2
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Phi-4
67.2
Ministral 3 3B (Reasoning)
59.7
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Phi-4 is ahead overall, 42 to 31. The biggest single separator in this matchup is HumanEval, where the scores are 82.6 and 16.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 53.8 versus 25.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Phi-4 has the edge for coding in this comparison, averaging 55 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Ministral 3 3B (Reasoning) has the edge for reasoning in this comparison, averaging 35.3 versus 31.3. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Phi-4 has the edge for agentic tasks in this comparison, averaging 38.3 versus 34. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Phi-4 has the edge for multimodal and grounded tasks in this comparison, averaging 46.8 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Phi-4 has the edge for multilingual tasks in this comparison, averaging 67.2 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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