this post was submitted on 13 Sep 2026
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Personally, the local model seems to be the future for AI within FOSS, and I think it may be refined to have lower usage requirements for a specific capability to run on smaller machines, not sure how much better general purpose models will get but after trying them, I expect modest progress over the next few years.
I don't trust the large frontier models and the push to build data centers, that's a grift at the expense of spending that could be useful elsewhere.
I'm lucky enough to have bought a 3090 2nd hand when they weren't insanely expensive in 2023. I'm trying "vibecoding" on my personal half-finished coding projects. My coding style is poor by most professional standards, but the edits I have had my local model (Qwen 3.8 27B UD Q4) and harness (llama.cpp and Opencode) spit out are reviewable to me, make logical sense, follows my existing conventions and does run correctly. I think it is by default on highest quality, which means writing one function takes 15m to an hour, but I'd rather it be slow and hallucinate in my code less. There are other optimizations I could make to have it run faster, but it's not a big deal to me. I can code the functions myself in less time, but what I think it is best at is catching bugs and my mistakes.
More or less my thought process so am not rewriting it. Local Qwen 3.8 27B Q8 produces useful output that saves development time. It's better at some things than others. It can save phenomenal amount of time in certain tasks like parsing codebases one's unfamiliar with. Same with documentation. Given that FOSS is mostly volunteer work, time saving tools tend to be a benefit, if the quality can be maintained. And quality can be maintained when one has that as a goal and not pushing the absolute maximum amoumt of code. Then there's also the tasks where quality doesn't matter beyond the happy path working, e.g. build scripts. FOSS has such wide positive effects that the ability to make more of it should be balanced against the cost of the tools.