alt Hacker News> are materially ahead of every open source model out there at this time
They aren't. Any difference is in sampling parameters and post-training flavor choices. These aren't things that are "materially ahead", that's basically just LLM themes.
> are materially ahead of every open source model out there at this time
They aren't. Any difference is in sampling parameters and post-training flavor choices. These aren't things that are "materially ahead", that's basically just LLM themes.
I’m sorry but you’re demonstrably incorrect.
Listen, I want more open weight models in the world. They create entrepreneurial opportunities and support use cases which the foundation labs don’t want to support.
But open weight models are consistently three to six months behind on performance compared to closed models, as confirmed by both benchmarks and personal use. They’re closer on coding and much further away on non-coding tasks.
There are theories as to why these models lag, which I won’t get into. But anyone claiming open-weight models are close to closed-weight models is ignoring significant evidence to the contrary.