Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 is clearly ahead on the aggregate, 88 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in coding, where it averages 81.8 against 6.2. The single biggest benchmark swing on the page is SWE-bench Pro, 85 to 5.
GPT-5.2 is also the more expensive model on tokens at $2.00 input / $8.00 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. GPT-5.2 is the reasoning model in the pair, while Ministral 3 3B 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. GPT-5.2 gives you the larger context window at 400K, compared with 128K for Ministral 3 3B.
Pick GPT-5.2 if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2
85.4
Ministral 3 3B
22.9
GPT-5.2
81.8
Ministral 3 3B
6.2
GPT-5.2
95
Ministral 3 3B
30.4
GPT-5.2
93.2
Ministral 3 3B
30.1
GPT-5.2
79.5
Ministral 3 3B
24.5
GPT-5.2
94
Ministral 3 3B
67
GPT-5.2
92.4
Ministral 3 3B
59.7
GPT-5.2
97.2
Ministral 3 3B
36
GPT-5.2 is ahead overall, 88 to 27. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 85 and 5.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 79.5 versus 24.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 81.8 versus 6.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for math in this comparison, averaging 97.2 versus 36. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for reasoning in this comparison, averaging 93.2 versus 30.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for agentic tasks in this comparison, averaging 85.4 versus 22.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for instruction following in this comparison, averaging 94 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multilingual tasks in this comparison, averaging 92.4 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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