I added this to a benchmark I've been doing of how well agents find security bugs, specifically security bugs originally found by Mythos. It performs poorly with only read/grep/ls tools, but in a follow-up test with a full shell and Python, it doubled its findings (still a poor showing, but it does at least indicate it is doing what it says on the tin: making tools to help it solve problems). It also did worse than Qwen AgentWorld, another recent post-train of Qwen 3.6 MoE intended for agentic use.

https://swelljoe.com/post/will-it-mythos/

I'd have expected this to get more HN attention. Qwen 3.6 35B capability in a 9B model is a bonkers claim.

Instead of training the model to directly answer questions we trained the model to always write and execute the code that would solve the question ?

If that is the case, this isn't just a fancy way to perform prompt optimization?