Different Searches in One Query API Request

Each prefetch runs exactly one search per one query.

Understand if user wants to run several parallel searches on:

1. The same vector representations but different queries or filters.
2. Different vector representations but the same raw query.

If first, help user to design logic of constructing query or/and filters on application side and then check Combining Searches. Don't forget to create indices on filterable payload fields, immediately after collection creation, prior to building HNSW, so filterable HNSW could be constructed.

If second, use named vectors, which allow to store multiple vector types per point in one collection. Beware that named vectors currently can be configured only at collection creation. To choose vectors, check following recommendations.

Missed Keyword Matches

Use when: pure vector search misses exact term or keyword matches and you need lexical retrieval alongside semantic search.

Most likely you need a sparse vector for exact text search alongside the dense one. Qdrant uses sparse vectors for lexical searches, as payload filtering doesn't provide any ranking score.