I'm out of the loop... so Qwen3-30B-VL is smart and Qwen3-30B is dumb... and that has to do not with the size but architecture?

Olmo author here, but I can help! First release of Qwen 3 left a lot of performance on the table bc they had some challenges balancing thinking and non-thinking modes. VL series has refreshed posttrain, so they are much better!

ahaha sorry that was unclear, while i think the VL version is maybe a bit more performant, by "dumb" i meant any low quant low size model you're going to run locally, vs a "smart" model in my book is something like Opus 4.1 or Gemma 3.

I basically class LLM queries into two categories, there's stuff i expect most models to get, and there's stuff i expect only the smartest models to have a shot of getting right, there's some stuff in the middle ground that a quant model running locally might not get but something dumb but acceptable like Sonnet 4.5 or Kimi K2 might be able to handle.

I generally just stick to the two extremes and route my queries accordingly. I've been burned by sonnet 4.5/gpt-5 too many times to trust it.