GLM-5 vs Laguna M.1

Pick GLM-5 if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.

GLM-5 is clearly ahead on the provisional aggregate, 67 to 51. 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 agentic, where it averages 56.2 against 45.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 56.2% to 45.8%.

GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna M.1. That is roughly Infinityx on output cost alone. Laguna M.1 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. GLM-5 gives you the larger context window at 200K, compared with 131K for Laguna M.1.