[dryarzeg]

That's quite a specific task for local models like these though (I mean mujoco), so it might be underrepresented in the training data or RL. I'm not sure if you will be able to see a significant leap in this direction in the next 0.5-2 years, although it's still possible.

[b89kim]

I’ve been testing these on other tasks—IK, Kalman filters, and UI/DB boilerplate. Qwen3.5 is multimodal and specialized for js/webdev or agentic coding. It’s not surprising MoE model have some limitations in specific area. I understand most LLM have limited ability in mathematical/physical reasoning. And I don't think these tasks represent general performance. I'm just sharing personal experiences for those curious.

[dryarzeg]

For me, the main issue with all kinds of recent "advancements" in LLMs is their lack in ability to generalize and extrapolate existing knowledge; they often can be quite weak when it comes to complex associations. Because while many LLMs can demonstrate sufficient theoretical knowledge in maths and physics - and by "sufficient" I mean at least postgraduate level - they often simply fail to apply this knowledge in fields that are closer to real life. At least, that's what I've seen from my experience. They're fine with theory, but once it comes to application, it's all messed up - even in their main "specializations" such as web development or other software-related tasks. And that's... kinda disappointing for me and even makes me a bit sad. We have a powerful tool, but we can't use it's true potential either because we're using it in the wrong way or because it's architecture cannot support this true potential.