Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GLM-4.5-Air is clearly ahead on the aggregate, 37 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.5-Air's sharpest advantage is in mathematics, where it averages 36.9 against 9.8. The single biggest benchmark swing on the page is MMLU, 35 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.
GPT-4.1 nano gives you the larger context window at 1M, compared with 128K for GLM-4.5-Air.
Pick GLM-4.5-Air 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.
GLM-4.5-Air
31
GPT-4.1 nano
65.2
GLM-4.5-Air
36.9
GPT-4.1 nano
9.8
GLM-4.5-Air
68
GPT-4.1 nano
83.2
GLM-4.5-Air is ahead overall, 37 to 23. The biggest single separator in this matchup is MMLU, where the scores are 35 and 80.1.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 31. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for math in this comparison, averaging 36.9 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 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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