Qwen is really good.
Also, generally, it makes sense. 8B models are generally not very good^.
That this 8B model is decent is impressive, but that it could perform on par with a good model 4 times as large is a daydream.
^ - To be polite. The small models + tool use for coding agents are almost universally ass. Proof: my personal experience. Ive tried many of them.
The geometric mean rule of thumb for MoE models is that the intelligence level of an MoE model with T total parameters and A active parameters is roughly equivalent to that of a dense model with sqrt(A*T) parameters. For qwen3.6-35B-A3B, that equivalent size is 10.24B, spitting distance of an 8B model. Good training can make up the 28% difference in size.
edit: It was a play on The Big Lebowski, folks.
Nor do class standings, nor hackerrank and the like.
What will tell you is asking them to fix a thing in your codebase. Once you ask an LLM to do that, a dozen times, I'd argue it's no longer "just your opinion man", it's a context-engineered performance x applicability assessment.
And it is very predictive.
But it's also why someone doing well at job A isn't necessarily going to be great at B, or bad at A doesn't mean will necessarily be bad at B.
I've often felt we should normalize a sort of mutual try-buy period where job-change seeker and company can spend a series of days without harming one's existing employment, to derisk the mutual learning. ESPECIALLY to derisk the career change for the applicant who only gets one timeline to manage, opposed to company that considers the applicant fungible.
But back to the LLM, yeah, the only valid opinion on whether it works for you is not benchmark, it's an informed opinion from 'using it in anger'.
Yes.
That is how you empirically evaluate tools; not by reading stupid benchmarks. By actually using the tools, for hours and hours. Doing real work.
Did you try using it? For hours? Do you use qwen?
How about you tell us about your experience with your great 8B models that you use daily. What coding agent harness do you have then hooked up to? What context size can you get before they lose track of whats happening? Do you swap between models for different coding tasks?
Or, have you not, actually, even actually tried any of this stuff, yourself?
Qwen3.6 raises the bar for models of its size. There really isn't a comparison in my opinion.
