Local models are not as sharp, and that is fine

A model running on your own laptop is almost always smaller than the big models running in a company's data center, and it shows. It may miss context, give a shorter answer, or need a clearer prompt to get anywhere useful. That is not a flaw in your setup. It is the tradeoff for keeping everything private and running on hardware you own. I keep a mental note of the kinds of prompts my local model handles well versus the ones where it visibly struggles.

The trick is matching the tool to the job. A local model handles a quick rewrite, a summary of your own notes, or a first pass on an idea just fine. Ask it to do deep research or handle a long, complicated document, and you will feel the gap right away.

Once you stop expecting a local model to match a cloud one, the disappointment goes away and you start using it for what it is actually good at.

Try this today: give your local model one small, well-defined task, like shortening a paragraph, and judge it only against that job.