Personally I find GLM-5.3 to be smart enough to be my daily driver, writing code, doing investigations, etc., including multi-codebase changes and finding the relevant documentation/supporting code for itself so I don't have to explain everything. It's fast (depending on your inference provider), cheap, and smart enough.

I find the full-size 5.3 is smart enough to avoid all the small-model problems, while GLM-5.3-Flash definitely starts showing its limits any time the task at hand is poorly defined. 5.3-Flash can often manage even complicated tasks, but the error rate (in terms of bad decisions, misunderstandings, etc) starts creeping up and the time wasted (or the risk thereof) gets high enough that it's worth just paying for the bigger model.

I do wish the bigger model could use vision though- that's currently limited to the flash model (presumably because it came out later, when they had figured out their vision training pipeline. Hopefully later releases will include it.)

Dunno, maybe I'm good at prompting it, but I haven't had many issues with GLM-5.3 Flash. After switching from the Claude models, I barely noticed any difference for most tasks. In fact, I have to recheck the settings from time to time to make sure I'm not running anything Anthropic when I see it working with sensitive data :)

The only annoying issue for me is that GLM-5.3 Flash is often eager to go into action and start modifying code when I've just asked a question and it misunderstood it as a call to action.