A frontier vision-language model can describe a picture of your living room but it can't tell you if your new couch will fit through the doorway. This is an important limitation in how today's multimodal models perceive the world. Most VLMs treat images as a flat grid of 2D pixels that get mapped into the same token space as text. That’s great at semantic pattern matching and identifying objects, but they lack a good way to represent depth, volume, and geometry. Recognizing what an object…