Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4o mini is clearly ahead on the aggregate, 52 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o mini's sharpest advantage is in coding, where it averages 65 against 6.2. The single biggest benchmark swing on the page is HumanEval, 87.2 to 15.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 3B. That is roughly Infinityx on output cost alone.
Pick GPT-4o mini if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if you want the cheaper token bill.
GPT-4o mini
50.9
Ministral 3 3B
22.9
GPT-4o mini
65
Ministral 3 3B
6.2
GPT-4o mini
60.2
Ministral 3 3B
30.4
GPT-4o mini
49.4
Ministral 3 3B
30.1
GPT-4o mini
62
Ministral 3 3B
24.5
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4o mini
74.7
Ministral 3 3B
59.7
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4o mini is ahead overall, 52 to 27. The biggest single separator in this matchup is HumanEval, where the scores are 87.2 and 15.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 62 versus 24.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 65 versus 6.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for reasoning in this comparison, averaging 49.4 versus 30.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for agentic tasks in this comparison, averaging 50.9 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multimodal and grounded tasks in this comparison, averaging 60.2 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 74.7 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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