I use a combination of a Claude Max subscription and local inference, including qwen3.8-27b, 4bit. I have found qwen to be absolutely useless at anything but very specific, surgical code changes. In my experience, for anything even remotely nuanced, a frontier model is required.
Index methodologies here: https://artificialanalysis.ai/evaluations/artificial-analysi...
Also see some specific benchmarks here: https://huggingface.co/Qwen/Qwen3.8-27B e.g. qwen scores 61.7 on swe bench pro, while opus 4.6 scores 53.4.
If you want to argue with the benchmarks, go for it. Fwiw i am not saying qwen3.8-27b is better or as good as the frontier. But i am saying it has crossed the threshold and is now a useful tool for coding and debugging. From my experience, Qwen3.6-35b-a3b was what you describe - it could do surgical edits only.
I think you're referring to a 5060Ti 16GB, yes?
32k context is easily done there. 64k can work with a more aggressive quant, but you lose a bit of speed.
But I don’t quite follow you - how does a more aggressive quant slow it down? Less bits per token means faster inference not slower.