Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 (medium) is clearly ahead on the aggregate, 78 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 (medium)'s sharpest advantage is in coding, where it averages 66.1 against 33. The single biggest benchmark swing on the page is SWE-bench Pro, 72 to 34.
GPT-5 (medium) 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 (medium) 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 (medium)
75.5
Ministral 3 14B
48.4
GPT-5 (medium)
66.1
Ministral 3 14B
33
GPT-5 (medium)
88.1
Ministral 3 14B
70.5
GPT-5 (medium)
84.3
Ministral 3 14B
63.6
GPT-5 (medium)
69.8
Ministral 3 14B
50.1
GPT-5 (medium)
88
Ministral 3 14B
80
GPT-5 (medium)
88.1
Ministral 3 14B
76.8
GPT-5 (medium)
92
Ministral 3 14B
69.7
GPT-5 (medium) is ahead overall, 78 to 55. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 72 and 34.
GPT-5 (medium) has the edge for knowledge tasks in this comparison, averaging 69.8 versus 50.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for coding in this comparison, averaging 66.1 versus 33. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for math in this comparison, averaging 92 versus 69.7. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for reasoning in this comparison, averaging 84.3 versus 63.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for agentic tasks in this comparison, averaging 75.5 versus 48.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for multimodal and grounded tasks in this comparison, averaging 88.1 versus 70.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for instruction following in this comparison, averaging 88 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for multilingual tasks in this comparison, averaging 88.1 versus 76.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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