GLM-5 vs Ornith-1.0-9B

Pick GLM-5 if you want the stronger benchmark profile. Ornith-1.0-9B only becomes the better choice if coding is the priority or you want the cheaper token bill.

GLM-5 is clearly ahead on the provisional aggregate, 66 to 52. 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 43.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 56.2% to 43.1%. Ornith-1.0-9B does hit back in coding, so the answer changes if that is the part of the workload you care about most.

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 Ornith-1.0-9B. That is roughly Infinityx on output cost alone. Ornith-1.0-9B 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. Ornith-1.0-9B gives you the larger context window at 262K, compared with 200K for GLM-5.