I have asked GLM4.7 in opencode to make an application to basically filter a couple of spatial datasets hosted at a url I provided it, and instead of trying to download read the dataset, it just read the url, assumed what the datasets were (and got it wrong) is and it's shape (and got it wrong) and the fields (and got it wrong) and just built an application based on vibes that was completely unfixable.

It wrote an extensive test suite on just fake data and then said the app is perfectly working as all tests passed.

This is a model that was supposed to match sonnet 4.5 in benchmarks. I don't think sonnet would be that dumb.

I use LLMs a lot to code, but these chinese models don't match anthropic and openai in being able to decide stuff for themselves. They work well if you give them explicit instructions that leaves little for it to mess up, but we are slowly approaching where OpenAI and anthropic models will make the right decisions on their own

this aligns perfecly with my experience, but of course, the discourse on X and other forums are filled with people who are not hands on. Marketing is first out of the gate. These models are not yet good enough to be put through a long coding session. They are getting better though! GLM 4.7 and Kimi 2.5 are alright.

It really is infuriatingly dumb; like a junior who does not know English. Indeed, it often transitions into Chinese.

Just now it added some stuff to a file starting at L30 and I said "that one line L30 will do remove the rest", it interpreted 'the rest' as the file, and not what it added.