Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 mini is clearly ahead on the aggregate, 69 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 mini's sharpest advantage is in reasoning, where it averages 81.8 against 69.2. The single biggest benchmark swing on the page is HumanEval, 80 to 62.
Pick GPT-5 mini if you want the stronger benchmark profile. Ministral 3 14B (Reasoning) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5 mini
65.7
Ministral 3 14B (Reasoning)
58.5
GPT-5 mini
42.8
Ministral 3 14B (Reasoning)
35
GPT-5 mini
83.8
Ministral 3 14B (Reasoning)
71.5
GPT-5 mini
81.8
Ministral 3 14B (Reasoning)
69.2
GPT-5 mini
62.8
Ministral 3 14B (Reasoning)
52.1
GPT-5 mini
82
Ministral 3 14B (Reasoning)
81
GPT-5 mini
80.1
Ministral 3 14B (Reasoning)
77.8
GPT-5 mini
87.2
Ministral 3 14B (Reasoning)
75.2
GPT-5 mini is ahead overall, 69 to 60. The biggest single separator in this matchup is HumanEval, where the scores are 80 and 62.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 52.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for coding in this comparison, averaging 42.8 versus 35. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for math in this comparison, averaging 87.2 versus 75.2. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for reasoning in this comparison, averaging 81.8 versus 69.2. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for agentic tasks in this comparison, averaging 65.7 versus 58.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multimodal and grounded tasks in this comparison, averaging 83.8 versus 71.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for instruction following in this comparison, averaging 82 versus 81. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multilingual tasks in this comparison, averaging 80.1 versus 77.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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