Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 nano is clearly ahead on the aggregate, 49 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 nano's sharpest advantage is in reasoning, where it averages 74.1 against 56.2. The single biggest benchmark swing on the page is AIME 2024, 9.8 to 86. o1-pro does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 1500.0x on output cost alone. o1-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 200K for o1-pro.
Pick GPT-4.1 nano if you want the stronger benchmark profile. o1-pro only becomes the better choice if mathematics is the priority or you want the stronger reasoning-first profile.
GPT-4.1 nano
47.4
o1-pro
39.7
GPT-4.1 nano
18
o1-pro
23
GPT-4.1 nano
59.3
o1-pro
48.5
GPT-4.1 nano
74.1
o1-pro
56.2
GPT-4.1 nano
50.7
o1-pro
69.9
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-4.1 nano
59
o1-pro
52
GPT-4.1 nano
9.8
o1-pro
86
GPT-4.1 nano is ahead overall, 49 to 45. The biggest single separator in this matchup is AIME 2024, where the scores are 9.8 and 86.
o1-pro has the edge for knowledge tasks in this comparison, averaging 69.9 versus 50.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o1-pro has the edge for coding in this comparison, averaging 23 versus 18. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1-pro has the edge for math in this comparison, averaging 86 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for reasoning in this comparison, averaging 74.1 versus 56.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for agentic tasks in this comparison, averaging 47.4 versus 39.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for multimodal and grounded tasks in this comparison, averaging 59.3 versus 48.5. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for multilingual tasks in this comparison, averaging 59 versus 52. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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