What's going on with Qwen3.6 27b? Filtered to Python it comes out at the top of the list, which seems... well, unlikely.
The Qwen3.6 models have memorized some common games. For example, if you ask it to create an index.html with a snake game, it will generate almost the same high quality snake game every time. The relatively low success rate of 25% but high average percentile of almost 100% for one-shot coding in Python suggests that the model is extremely good at few tasks.
That's why a lot of people have been freaking out about local LLMs since april. There's finally a decent model that runs locally on a GPU or two that can do agentic programming at a reasonable enough tokens per second.
I've found that the Q5+ quants are less loopy than Q4. Still not perfect, but noticeably better.
> reasonable enough tokens per second
The speed has been amazing. I've been running the recent llama.cpp MTP branch with an uncensored variant of Qwen3.6-35B-A3B on my RTX 3090 over 170 tokens per second and it was able to turn a buffer overflow into a reliable shell exploit in just a few seconds (with reasoning disabled). Still a bit loopy though. Hopefully, the Qwen team will pay more attention to those looping issues. It feels like their models are especially susceptible.
Note that the MTP PR https://github.com/ggml-org/llama.cpp/pull/22673 is still under development, so things might be broken.