Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Claude 4.1 Opus Thinking is clearly ahead on the aggregate, 39 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 4.1 Opus Thinking's sharpest advantage is in mathematics, where it averages 40.1 against 9.8. The single biggest benchmark swing on the page is MMLU, 38 to 80.1. GPT-4.1 nano does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude 4.1 Opus Thinking 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 Claude 4.1 Opus Thinking.
Pick Claude 4.1 Opus Thinking if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Claude 4.1 Opus Thinking
34
GPT-4.1 nano
65.2
Claude 4.1 Opus Thinking
40.1
GPT-4.1 nano
9.8
Claude 4.1 Opus Thinking
66
GPT-4.1 nano
83.2
Claude 4.1 Opus Thinking is ahead overall, 39 to 23. The biggest single separator in this matchup is MMLU, where the scores are 38 and 80.1.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 34. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Claude 4.1 Opus Thinking has the edge for math in this comparison, averaging 40.1 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 instruction following in this comparison, averaging 83.2 versus 66. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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