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 36. 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 multimodal & grounded, where it averages 83.8 against 33.4. The single biggest benchmark swing on the page is MMMU-Pro, 86 to 28.
Pick GPT-5 mini if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5 mini
65.7
Ministral 3 8B (Reasoning)
38.5
GPT-5 mini
42.8
Ministral 3 8B (Reasoning)
15.2
GPT-5 mini
83.8
Ministral 3 8B (Reasoning)
33.4
GPT-5 mini
81.8
Ministral 3 8B (Reasoning)
42.1
GPT-5 mini
62.8
Ministral 3 8B (Reasoning)
30
GPT-5 mini
82
Ministral 3 8B (Reasoning)
70
GPT-5 mini
80.1
Ministral 3 8B (Reasoning)
61.7
GPT-5 mini
87.2
Ministral 3 8B (Reasoning)
47.8
GPT-5 mini is ahead overall, 69 to 36. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 28.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 30. 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 15.2. 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 47.8. 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 42.1. 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 38.5. 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 33.4. 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 70. 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 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.