Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GLM-4.5 has the cleaner overall profile here, landing at 38 versus 35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-4.5's sharpest advantage is in mathematics, where it averages 38.6 against 23.1. The single biggest benchmark swing on the page is MMLU, 37 to 87.5. GPT-4.1 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini gives you the larger context window at 1M, compared with 128K for GLM-4.5.
Pick GLM-4.5 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
GLM-4.5
32.2
GPT-4.1 mini
75.9
GLM-4.5
20
GPT-4.1 mini
23.6
GLM-4.5
38.6
GPT-4.1 mini
23.1
GLM-4.5
68
GPT-4.1 mini
88.5
GLM-4.5 is ahead overall, 38 to 35. The biggest single separator in this matchup is MMLU, where the scores are 37 and 87.5.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 32.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for coding in this comparison, averaging 23.6 versus 20. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GLM-4.5 has the edge for math in this comparison, averaging 38.6 versus 23.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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