Ornith is a nice fine-tune of Qwen that works reasonably well on reasonable hardware, Bonsai also seems to be often recommended but I haven’t tried it personally. That said, from everything I’ve seen local agentic code is pretty computationally wasteful in many cases, it iterates heavily and confuses itself a lot and self-corrects often repeatedly. It hurts my soul to imagine the energy waste and environmentally damage if large numbers of people started using this routinely and carelessly.
It is meaningfully useful, I’ll grant you that, and when paired with highly specific and well-bounded tasks it performs quite well. I hate the idea of relying on it too heavily though. If you just throw it at things blind and without you also providing assistance to the model, it will get the job done, eventually, just in a really painful and stupid way. It’s not Claude, but for a locally-running substitute it’s remarkably good, it handles coding assistance very effectively, but it’s a very poor coder when operating completely independently. I find the best and most efficient use is to ask it for suggestions, keeping the pieces as small as reasonably possible, and then implement them myself based on what it suggests (either adjusting the model’s edits or copy-pasting the model’s suggestions). It’s very good at locating the relevant code and it usually suggests a reasonable design, which I typically tweak based on my own experience. Maybe that makes me old-school, maybe I’m a luddite, but that’s what my experience tells me to do. If you don’t have any experience, I guess you’re on your own, good luck with the models. They’re decent, but they’re not brilliant programmers (granted neither am I most days). That’s my opinion and I’m sticking with it until I see evidence to suggest otherwise.






I don’t actually think benchmarks are fully reliable. They give you some idea of the model’s performance but there is also value in some models that aren’t necessarily reflected on every (or any) benchmark.