GLM-5 vs GPT-5.4 nano

Pick GLM-5 if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill or you need the larger 400K context window.

GLM-5 is clearly ahead on the provisional aggregate, 67 to 59. 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 knowledge, where it averages 70.7 against 53.2. The single biggest benchmark swing on the page is HLE, 50.4% to 37.7%.

GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 2.6x on output cost alone. GPT-5.4 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-5.4 nano gives you the larger context window at 400K, compared with 200K for GLM-5.