Retrieval starts by embedding the user's question with the same embedding model that produced the chunk vectors. Because both the question and the chunks pass through one model, the question becomes a vector in the same meaning space as the stored chunks, and can be placed as a point among them. A question embedded by a different model would land in an unrelated coordinate system, so the vectors would not be comparable.
How AI Answers Questions About Documents It Never Learned