Local models are extraordinarily expensive if you're not maximizing throughput, and you're not going to be maximizing it.

Local models need to be resident in expensive RAM, the kind that has fat pipes to compute. And if you have a local app, how do you take a dependency on whatever random model is installed? Does it support your tool calling complexity? Does it have multimodal input? Does it support system messages in the middle of the conversation or not? Is it dumb enough to need reminders all the time?

Spend enough time building against local models and you'll see they're jagged in performance. You need to tune context size, trade off system message complexity with progressive disclosure. You simply can't rely on intelligence. A bunch of work goes into the harness.

Meanwhile, third party inference is getting the benefits of scale. You only need to rent a timeslice of memory and compute. It's consistent and everybody gets the same experience. And yes, it needs paying for, but the economics are just better.

> And if you have a local app, how do you take a dependency on whatever random model is installed?

Reading the tea leaves here, it will probably be common for OS’s to have built in models that can be accessed via API. Apple already does this.

I don't know why you are being downloaded. These are precisely the facts that advocates for local models completely ignore.

Local models are absolutely going to be the future for things like simple automation and classification tasks that run occasionally and don't need to rely on internet access.

But for all of the serious stuff where you are doing knowledge work, the models will simply continue to be too big, and too slow to run locally.

The article says:

> Use cloud models only when they’re genuinely necessary.

But at least for me, they're genuinely necessary for 99+% of my LLM usage.

At the end of the day, the constraint here really is efficiency and cost.

Privacy can be ensured with the legal system, the same way that businesses that compete with Google still have no problem storing their data in Google Workspace and Google Cloud. The contractual guarantees of privacy are ironclad, and Google would lose its entire cloud business overnight as its customers fled if it ever violated those contractual agreements (on top of whatever penalties they allow for).

> And if you have a local app, how do you take a dependency on whatever random model is installed?

Why not ship your own model? In the age of Electron apps, 10GB+ apps are not unheard of.