Sorry but you're just seeing what you want to see. The idea that a 31b model is anywhere even in the ballpark of something like Opus 4.5 is just absurd on its face.
False. The absolute capability is irrelevant, with the proper harness 31b is more than adequate for a very large portion of the tasks I ask AI to do. The metric isn't how good the model is at Erdos Problems, it's how reliably it can remove drudgery in my life. It just autonomously reverse engineered a bluetooth protocol with minimal intervention, it's ability to react to data and ground itself is constantly impressive to me. I do a ton of testing with these models, today I had Gemma answer a physics problem that Opus 4.7 gave up on. With a decent harness and context the set of tasks where their capabilities are both good enough is very surprising. The tasks I have that stump Gemma often also stump Opus 4.7.
No, it isn't. I am saying that the set of tasks that can be completed by Opus 4.7 has a surprisingly large overlap with the set of tasks that can be completed by Gemma 31B. It is meaningfully equivalent in many cases.
(of course if i'm being honest 640kB is fine, i'm sure tons of the world's commerce is handled by less for example, the delta between a system with 640kb of ram and a modern one is near nil for many people, the UX on a PoS terminal does not require more than that for example, the hacker news UX could also be roughly the same)
How refreshing to hear this kind of old-school hacker thinking, in a thread where most people have given up on local computing in exchange for convenience and permanent third-party dependency.
With embedded systems affordable and ubiquitous, hopefully a growing segment of the new generation will also learn to push the limit of available hardware and see how far we can take it. As an engineer there's a satisfaction in solving things with what you got.
There's a new technique, 1-bit family of language models that can achieve up to 9x memory efficiency compared to existing models. Still multiple gigabytes for practical use I imagine, but it's great progress toward local AI, which I believe will be common in the near future. https://prismml.com/news/ternary-bonsai