Another example that the harness, more than the model itself, decides how far intelligence actually gets.

With the API alone, execution ends when the model stops.

@atomicagent_io, a model-agnostic agent layer, made GLM 5.3 better and it costs only 77 cents more.

It kept the run alive, executed the model's actions, feeds failures back, preserves state, and decides when the loop should stop.

In these 3 prompts, that roughly doubled token usage, but added only $0.77 to the total cost.

Outputs:
✦ GLM 5.3, API only: 543,290 tokens, $2.39
✦ GLM 5.3 + Atomic Agent: 1,091,380 tokens, $3.16

There is a big difference between asking a model once and letting a model work. And a model-agnostic agent layer sits exactly on that boundary.