[dagmx]

Your first sentence has the fallacy that you’re attributing the cost of the device to a single feature against the cost of that single feature.

Most people are unlikely to buy the device for the AI features alone. It’s a value add to the device they’d buy anyway.

So you need the paid for option to be significantly better than the free one that comes with the device.

Your second sentence assumes the local one is dumb. What happens when local ones get better? Again how much better is the cloud one to compete on cost?

To your last sentence, it assumes data fetching from the cloud. Which is valid but a lot of data is local too. Are people really going to pay for what Google search is giving them for free?

[mupuff1234]

I think it's a more likely assumption that on device performance will trail off device models by a significant margin for at least the next few years - of course if magically you can make it work locally with the same level of performance it would be better.

Plus a lot of the "agentic" stuff is interaction with the outside world, connectivity is a must regardless.

[dagmx]

My point is that you do NOT need the same level of performance. You need an adequate level of performance that the cost to get more performance isn’t worth it to most people.

[mupuff1234]

And my point is that it's way too early to try to optimize for running locally, if performance really stabilizes and comes to a halt (which may likely happen) then it makes more sense to optimize.

Plus once you start with on device features you start limiting your development speed and flexibility.

[_ea1k]

It isn't really hypothetical. Lots of good models run well on a modern Macbook Pro.