Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GLM-5 is clearly ahead on the aggregate, 74 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in mathematics, where it averages 86.4 against 85.2. The single biggest benchmark swing on the page is GPQA, 86 to 71.2.
GPT-5 nano is the reasoning model in the pair, while GLM-5 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-5 nano gives you the larger context window at 400K, compared with 200K for GLM-5.
Pick GLM-5 if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if you need the larger 400K context window or you want the stronger reasoning-first profile.
GLM-5
71.2
GPT-5 nano
71.2
GLM-5
86.4
GPT-5 nano
85.2
GLM-5 is ahead overall, 74 to 31. The biggest single separator in this matchup is GPQA, where the scores are 86 and 71.2.
GLM-5 and GPT-5 nano are effectively tied for knowledge tasks here, both landing at 71.2 on average.
GLM-5 has the edge for math in this comparison, averaging 86.4 versus 85.2. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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