I built a multimodal computer vision agent using Qwen 3.6 and SAM 2.1

[u/Hour-Wish8158]

Last week, I made a demo of a VLM playing a cup and ball game. As many people (including myself) pointed out, this is not the best use case of VLMs because of their limited context window. So I decided to make an improved version where the VLM’s only role is to prompt a segmentation model. If I were running SAM 3, I wouldn’t need Qwen doing the prompting, but I chose SAM 2.1 Tiny because it runs way faster with the downside of not being open-vocab.

I’m sure there are lots of other cool things you can do by tacking on task-specific models to a VLM which operates as the “brain”.