One thing though, the actual prompt I used was pretty long (844 words), and ... generated by GPT-5.6 Sol (lol), with the intent of "benchmarking" model performance in being able to write stories where the model avoids explicitly stating every detail in the prompt.
I wonder if the GPT-produced stream could steer the generation into GPT-think territory. That's all I've got, though.
Then there's the actual geometry problem from the stolen thoughts paper:
Let ABCDE be a convex pentagon with AB=14, BC=7, CD=24, DE=13, EA=26, and ∠B=∠E=60◦. For f(X)=AX+BX+CX+DX+EX, the least value of f(X) is m+n√p (p squarefree). Find m+n+p.That's the default and I'm sure almost everyone else is also using it because other reasoning efforts yield subpar results from what I've seen.
I think it is clear that medium reasoning has more 'loopy' results like the older Qwens, but I actually think the low effort results are usually more appropriate.
If you plan to one-shot and vibe code AI slop to meet benchmarks, maybe xhigh makes sense. But if you want a responsive agentic coding assistant it is, to me, quite evidently the wrong choice, especially on modest hardware.
I have seen xhigh radically distract itself with rabbitholes and write considerably worse code than low.
It is my own opinion only, but I think much of the fuss about squeezing Qwen 3.8 27B into small local hardware setups, Macs etc., is a bit misguided.
There's too much focus on its benchmark scores, its one-shot capability, canned demos etc.
For my own needs Muse Glimmer (again on reasoning strength: low) is shaping up to being the more practical agentic tool. It is considerably faster than Qwen at solving real coding tasks.