Local privacy respecting inference can be worth it. I use a local model to log everything I do all week to automate my timesheet. I also have it do a bunch of other data tasks. I won't say that larger SOTA models wouldn't do these tasks better than a local model but PII is a concern and my employer wouldn't approve of me just setting tokens on fire everyday to do what I could do myself.

> more work for the user

Model routers allow this to happen automatically without any more work by the user.

> a shittier model

A ton of tasks don't require the most expensive frontier models, etc.

> I’m not sure why anyone does it

1. Faster solutions from the LLM - also reduces employee costs of having the employee waiting on the LLM

2. Avoiding things like the half-billion dollar per month bill for a single company’s LLM use recently reported in Axios

I sometimes let Claude Opus create plans, DeepSeek v4 pro implements and writes tests. Claude reviews and corrects.

Saves like $2-3 per session. Same quality code.

What you call a shittier model is what was considered frontier and fantastic one generation ago…