@bilboed yeah, totally agree. Going further Im actually surprised LLM like https://allenai.org/olmo is not more common in FOSS circles , which is not only openweight but the data to train it is open as well (even if is not as good as others but still I think is more aligned with Foss)

@jjardon Great, you've nerdsnipped me. I'll give olmo a try. Was already using the various qwen models, mistral ones, and apertus (all local).

As for "not as good", the question is really "good at what" and "good as what" ?

Obviously, local/open models aren't going to be as "good" at deep knowledge as models 100 or 200 times their size. And which have been trained on more content. But do you really need a system that can reliably spit out that obscure specification virtually no-one uses, or do you need it to have a good enough common base of knowledge and reasoning, so that it can be useful on the context you provide it ?

A lot of current open models are great for summarizing, brainstorming, searching (in your codebase or knowledge base), reasoning, translating, spellchecking, ... That alone is a great way to gain time.

A lot are also becoming multi-modal also, I.e. can understand and reason on an image (a design you scribbled on a piece of paper or a whiteboard, a screenshot of a failing web page). Add speech to text and text to speech and we have a system that can (locally) help impaired users !