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 55. 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 63.6. The single biggest benchmark swing on the page is HumanEval, 80 to 58.
GPT-5 mini 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 GPT-5 mini 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.
GPT-5 mini
65.7
Ministral 3 14B
48.4
GPT-5 mini
42.8
Ministral 3 14B
33
GPT-5 mini
83.8
Ministral 3 14B
70.5
GPT-5 mini
81.8
Ministral 3 14B
63.6
GPT-5 mini
62.8
Ministral 3 14B
50.1
GPT-5 mini
82
Ministral 3 14B
80
GPT-5 mini
80.1
Ministral 3 14B
76.8
GPT-5 mini
87.2
Ministral 3 14B
69.7
GPT-5 mini is ahead overall, 69 to 55. The biggest single separator in this matchup is HumanEval, where the scores are 80 and 58.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 50.1. 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 33. 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 69.7. 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 63.6. Inside this category, LongBench v2 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 48.4. Inside this category, Terminal-Bench 2.0 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 70.5. 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 80. 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 76.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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