Comment by The_Goonies1985
7 hours ago
The author mentions a C codebase. Is AI good at coding in C now? If so, which AI systems lead in this language?
Ideally: local; offline.
Or do I have to wrestle it for 250 hours before it coughs up the dough? Last time I tried, the AI systems struggled with some of the most basic C code.
It seemed fine with Python, but then my cat can do that.
C is actually one of the better supported languages for AI assistants these days, a lot better than it was a year or two ago. The hallucination of APIs problem has improved alot. Models like Claude Sonnet and Qwen 2.5 Coder have much stronger recall of POSIX/stdlib now. The harder remaining challenge with C is that AI still struggles with ownership and lifetime reasoning at scale. It can write correct isolated functions but doesnt always carry the right invariants across a larger codebase, which is exactly the architecture problem the article describes.
For local/offline Qwen 2.5 Coder 32B is probably your strongest option if you have the VRAM (or can run it quantized). Handles C better than most other local models in my experience.
Thanks Morpheus_Matrix. I'll take a look at Qwen 2.5 Coder 32B for offline C. I appreciate your guidance.
By extraordinary coincidence, I was just a moment ago part-of-the-way through re-watching The Matrix (1999) and paused it to check Hacker News. There your reply greeted me.
Wild glitch!
There is also a successor to that: Qwen3-Coder-Next, which is a newer and bigger model, but it obviously requires more hardware resources, being an 80B model.
However it is likely to be the most powerful open weights coding assistant that you can run locally, without having to worry about token price or reaching the subscription limits in the most inconvenient moment.