I will LOL for the day when a LLM will just "let me look for API keys on Github" and finds a few for rate-limited APIs like Octopart, Mouser, etc.
Anyhow, I don't expect code from LLMs to be of amazing standard. But most code shouldn't be written like its your life work. It should implement a feature, in an easy to read way, with good maintability. When projects grow, its usually hard to keep an overview if you're working alone.
Fwiw:
This is one of the first things I tried to use OpenCode for. I have about 44K LOC project here (18K main, 8.5K infrastructure, 15K test and the rest are sandbox/tools), and it does a fair job at finding code smells for me and making suggestions for large refactors.
Since my last post, I moved over from OpenCode as GUI to OpenChamber. Its not completely bump/bug-free, but at least I get prompted before running a particular tool (like bash or editing files). It also seems to automatically delegate smaller tasks to subagents like "explore" which run in a new context, and thus run faster.
I switched over from Qwen3.5/Qwen3Coder to Gemma4 31B. Iirc Qwen3.5 is a Mixture of Experts model, which means only a few B parameters are active at a time. It ran fast but was hallucinating like crazy. It spend a full hour running in circles adding code, seeing the build fail, then making silly changes and eventually giving up. Then when I gave suggestions how to fix it, it just tossed everything and "tried again".
Gemma 4 seems to be making very solid forward progress. Although I've seen with others that Claude 4.6 Sonnet is still much more capable. Unfortunately, in their infinite wisdom, Anthropic only accepts Credit Card payments which as an European I obviously don't have. So maybe I will sign up to Claude via GooglePay some day, just to compare, or have it hack away at the more complex/architecture drafting tasks. Not every task needs to be most complex/expensive model.
I will say that "write a compiler" was beyond the local models I tried - and I'm running on a Macbook M4 Max with 128GB of RAM so I could play with some large local models. 122B Qwen3-Coder 3.5 was the best of the bunch, but it still wasn't even close to the Claude results. Night and day.
122B on 128GB of RAM? Is that Q4 with a limited context size?
I tried Qwen3 80B and that was really stretching my system thin. I still allocate 96GB as VRAM, and it couldn't really handle context sizes much beyond 100K. And that is a problem on a medium-large project when the prompts get so big it has to prune 2/3s for every intermediate prompt..
Afaik AI models also move very very quickly still, despite apparent plateau of capability. They do get increasingly better and more efficient with a similar amount of weights. Unfortunately open models are still 0.5 - 1 year behind, so it is exciting to know that cutting edge Claude models will probably run local by this christmas. Then again Claude's holding back Mythos because its "too powerful" does spark my interest to try that as well... if we ever get to see it.