Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 13.8. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 17.
GPT-5.2 Pro is the reasoning model in the pair, while MiniMax M1 80k 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 Pro gives you the larger context window at 400K, compared with 80K for MiniMax M1 80k.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. MiniMax M1 80k only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
MiniMax M1 80k
32.1
GPT-5.2 Pro
84.8
MiniMax M1 80k
13.8
GPT-5.2 Pro
96
MiniMax M1 80k
39
GPT-5.2 Pro
95.2
MiniMax M1 80k
41.7
GPT-5.2 Pro
81.5
MiniMax M1 80k
31.3
GPT-5.2 Pro
95
MiniMax M1 80k
68
GPT-5.2 Pro
93.4
MiniMax M1 80k
59.1
GPT-5.2 Pro
98.2
MiniMax M1 80k
44.9
GPT-5.2 Pro is ahead overall, 90 to 35. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 17.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 31.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 13.8. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 44.9. Inside this category, HMMT Feb 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 41.7. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 32.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 39. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 59.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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