> Introducing Ripple-65B Preview, a Frontier Open-Weight Model
It's not "frontier", it's not "frontier" even in the category of open-weight models (though usually that phrasing would mean frontier over all, and also open weight)... it's only "frontier" in the small sub-category of US made open-weight models.
Being at the Pareto frontier means that you can't get something better on one aspect without compromising on some other aspect. The trick is that it is easy to be at the Pareto frontier by having enough dimensions.
Here, we have 4: score, number of parameters, origin (US) and open-weight. You can get a better score or a lower number of parameters, but you have to compromise on at least one of the other aspects. That's a pretty weak frontier if you ask me.
(You could say that “ability to be trusted by US government/military users” is quantifiable, but I would argue that by that metric, this model falls behind non-US-originated open-weight models that have more eyes on them!)
By that logic, any model is a frontier model. My GPT-2 clone is a frontier model when you compare it against models that were trained on my homelab.