From a fair bit of coding with the agent, my experience with Qwen 3.8 (Qwen3.8-Flash-Next-GSQ-RCO-IQ3_S-0 on Strata, Qwen 3.8 27B on ninfer). In my particular case, I was trying to clone a recent HN post which allowed you to visualize how out of tune your singing was relative to a song, but as a web app or portable native app.
My experience is that both those models will generate an enormous amount of noise (literally: it was running audible unit tests on my machine to test the note-detection algorithms) while coming to a solution, if they do find a solution- while Claude (whatever the latest model is) or ChatGPT (ditto) will do 1/10th the amount of work to get the right solution. I suspect if I had the resources to run GLM 5.3, it would probably be significantly faster to get to a working solution than Qwen-3.8 27B, but likely still somewhat inferior to Claude or ChatGPT solutions, and also would generate a much larger energy bill on my part.