alt Hacker News> It is absolutely not comparable to frontier models.
This is not said often enough.
Yes, local LLMs are great! But reading most HN posts on the subject, you'd think they're within reach of Opus 4.7.
There is a very small, very vocal, very passionate crowd that dramatically overstates the capabilities of local LLMs on HN.
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This.
I have seen way too many people who are overly optimistic about local LLMs.
Having spent a decent amount of time playing with them on consumer nvidia GPUs, I understand well that they not going to be widely usable any time soon. Unfortunately not many people share that.
At least in my experience, local models are very far away from models like Opus 4.7 or ChatGPT 5.5 in coding and problem solving areas.
I find them useful in basic research and learning and question asking tasks. Although at the same time, a Wikipedia page read or a few Google searches likely could accomplish the same and has been able to for decades.
Very different from my experience, Gemma 31b just solved a physics problem Opus 4.7 gave up on. I definitely don't think they're equivalent in general, Opus for sure is way smarter and way more likely to get things right on the edge, but it's still quite likely to get things wrong too it doesn't make it that useful for a lot of stuff. Conversely there are so many things that you would use an LLM for that they will both reliably oneshot. Especially in agentic mode where you have ground truth feedback between turns the difference gets quite small for a lot of tasks.
That all being said I've spent hundreds (maybe thousands?) of hours on this stuff over the past few years so I don't see a lot of the rough edges. I really believe capability is there, Gemma 4 31B is a useful agent for all sorts of stuff, and anything you can reasonably expect an LLM to oneshot Qwen 3.6 35b MoE will handle at like 90tok/sec, absolutely fantastic for tasks that don't require a huge amount of precision.