[magicalhippo]

A local model is an open model you run locally, so I'm not entirely sure the distinction in the question makes sense.

That said, if you're talking about models you can actually use on a single regular computer that costs less than a new home, the current crop of open models are very capable but also have noticeable limitations.

Small models will always have limitations in terms of capability and especially knowledge. Improved training data and training regiment can squeeze out more from the same number of weights, but there is a limit.

So with that in mind, I think such a question only makes sense when talking about specific tasks, like creative writing, data extraction from text, answering knowledge questions, refactoring code, writing greenfield code, etc.

In some of these areas the smaller open models are very good and not that far behind. In other areas they are lagging much more, due to their inherent limitations.

[myk-e]

Yes, I meant ordinary hardware which you find at home, like a current MacBook Air or equivalent Windows desktop. There must be a time frame when early SOTA LLMs were at a level that compares to open models that can run on ordinary hardware. But it's more like years rather than months. My rough guess would be 2-3 years. Which still would be amazing if we could get OPUS 4.5 quality within 2-3 years on an ordinary computer.

[karmakaze]

I don't know if you'd consider this ordinary, but a single Mac Studio M5 Ultra 512GB (or even 256GB) V/RAM seems pretty sweet.

[myk-e]

I love the spec, but it is like 5x or 10x a Macbook Air I mean really ordinary, Personal Computer in broad sense - not dedicated LLM kit.