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 49. 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 mathematics, where it averages 98.2 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 99 to 9.8.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 375.0x on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while GPT-4.1 nano 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-4.1 nano gives you the larger context window at 1M, compared with 400K for GPT-5.2 Pro.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.2 Pro
85.9
GPT-4.1 nano
47.4
GPT-5.2 Pro
84.8
GPT-4.1 nano
18
GPT-5.2 Pro
96
GPT-4.1 nano
59.3
GPT-5.2 Pro
95.2
GPT-4.1 nano
74.1
GPT-5.2 Pro
81.5
GPT-4.1 nano
50.7
GPT-5.2 Pro
95
GPT-4.1 nano
83.2
GPT-5.2 Pro
93.4
GPT-4.1 nano
59
GPT-5.2 Pro
98.2
GPT-4.1 nano
9.8
GPT-5.2 Pro is ahead overall, 90 to 49. The biggest single separator in this matchup is AIME 2024, where the scores are 99 and 9.8.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 50.7. 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 18. 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 9.8. Inside this category, AIME 2024 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 74.1. Inside this category, MRCRv2 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 47.4. 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 59.3. 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 83.2. 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. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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