Even if they do get better. The latest closed-source {gemini|anthropic|openai} model will always be insanely good and it would be dumb to use a local one from 3 years back.
Also tooling, you can use aider which is ok. But claude code and gemini cli will always be superior and will only work correctly with their respective models.
I don’t know about your first point: at some point the three-year difference may not be worth the premium, as local models reach “good enough.”
But the second point seems even less likely to be true: why will Claude code and Gemini cli always be superior? Other than advantageous token prices (which the people willing to pay the aforementioned premium shouldn’t even care about), what do they inherently have over third-party tooling?
Even using Claude Code vs. something like Crush yields drastically different results. Same model, same prompt, same cost... the agent is a huge differentiator, which surprised me.
I totally agree that the agent is essential, and that right now Claude Code is semi-unanimously the best agent. But agentic tooling is written, not trained (as far as I can tell—someone correct me) so it’s not immediately obvious to me that a third-party couldn’t eventually do it better.
Maybe to answer my own question, LLM developers have one, potentially two advantages over third-party tooling developers: 1) virtually unlimited tokens, zero rate limiting with which to play around with tooling dev. 2) the opportunity to train the network on their own tooling.
The first advantage is theoretically mitigated by insane VC funding, but will probably always be a problem for OSS.
I’m probably overlooking news that the second advantage is where Anthropic is winning right now; I don’t have intuition for where this advantage will change with time.
Depends on your use case though. You don't always need the best. Even if you have a hypercar, you probably drive a regular car to work.
There's also a personal good enough point for everyone who's hoping to cut the cord and go local. If local models get as good as current moments Claude Sonnet, I would actually be totally fine using that locally and riding the local improvements from then on.
And for local stuff like home automation or general conversational tasks, local has been good enough for a while now. I don't need the hypercar of LLMs to help me with cooking a recipe for example.
> Even if they do get better. The latest closed-source {gemini|anthropic|openai} model will always be insanely good and it would be dumb to use a local one from 3 years back.
If they use a hosted model, they’ll probably pin everything initially to, at best, the second newest model from their chosen provider (the newest being insufficiently proven) and update models to something similarly behind only when the older model goes completely out of support.
I use Claude Code with other models sometimes.
For well defined tasks that Claude creates, I'll pass off execution to a locally run model (running in another Claude Code instance) and it works just fine. Not for every task, but more than you might think.