It’s a reasoning model so that’s what it’s supposed to do. It makes it more accurate with math and a slew of other things. It’s usually meant to be processed somehow so only the final output is shown
You can install n8n and and use it with Ollama to create some pretty cool chat workflows
Depending on what you want to do with it, and what your expectations are; the smaller distilled versions could work on CPU, but most likely will need extra help on top, just like other similar sized models.
This being a reasoning model, you might get a more well thought out results out of it, but at the end of the day, smaller parameter space (easiest to think as ‘less vocabulary’), smaller capabilities.
If you just want something to very quickly chat back and forth with on a CPU, try IBM’s granite3.1-moe:3b, which is very fast even on a modern CPU, but doesn’t really excel in complex problems without additional support (ie: RAG or tool use).
My primary use would probably be a model for home assistant to reason what was said, and based reason what is desired like "Turn off all outlets" being said in the living room would turn them off. Or saying "its cold" to adjust the thermostat. Also hoping it would be able to figure out speech to text inaccuracies and reason what is wanted still. I think a smaller model would be an appropriate use for this also since response times should be on the quicker side.