Can two points in the same Qdrant collection have vectors of different dimensionality?

For a given dense vector space in a Qdrant collection, points must conform to the configured dimensionality. A query vector must also match that vector space's dimension.

This constraint exists because the index and distance computation operate in a defined vector space. Allowing arbitrary dimensions within one vector field would make the metric and index structure ambiguous.

Named vectors provide the escape hatch when one logical point needs different dimensions: each named vector is a separate configured vector space. For example, an image vector can be 512 dimensions while a text vector is 768 dimensions on the same point.

A common mistake is assuming one collection means one dimension globally. That is true for a single unnamed dense vector configuration, but named vectors allow multiple independently configured vector spaces in the same collection.