Good question. I agree with what I think you're implying, which is that local generation is not the right choice if you want to maximize results per time/$ spent. In my experience, hosted models like Claude Opus 4.6 are just so effective that it's hard to justify using much else.

Nevertheless, I spend a lot of time with local models because of:

1. Pure engineering/academic curiosity. It's a blast to experiment with low-level settings/finetunes/lora's/etc. (I have a Cog Sci/ML/software eng background.)

2. I prefer not to share my data with 3rd party services, and it's also nice to not have to worry too much about accidentally pasting sensitive data into prompts (like personal health notes), or if I'm wasting $ with silly experiments, or if I'm accidentally poisoning some stateful cross-session 'memories' linked to an account.

3. It's nice to be able solve simple tasks without having to reason about any external 'side-effects' outside my machine.