GLM-5 vs o1

Pick GLM-5 if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.

GLM-5 is clearly ahead on the provisional aggregate, 67 to 58. 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 instruction following, where it averages 92.6 against 92.2. The single biggest benchmark swing on the page is GPQA, 86% to 75.7%. o1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 18.8x on output cost alone. o1 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.