Comparison
Hybrid Search vs Semantic Search
Hybrid Search and Semantic Search are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Hybrid Search
Almost any production RAG; the wins are essentially free once your vector DB supports it.
A code-search RAG: vector finds "the file that does X" semantically, BM25 finds files containing the exact function name; hybrid catches both.
When you would reach for Semantic Search
Semantic Search comes up when the question is fundamentally about agents & tools.
Searching "cars under 10k" matches "vehicles below ten thousand dollars."
Frequently asked
What is the difference between Hybrid Search and Semantic Search?
Hybrid Search: Hybrid search combines vector (semantic) and keyword (BM25) retrieval and fuses their results — usually via Reciprocal Rank Fusion — to get the best of both: semantic recall and exact-match precision. Semantic Search: Semantic search ranks documents by meaning rather than keyword match, using embedding similarity. "Affordable laptops" can match "cheap notebooks" even with no overlapping words.
When should I use Hybrid Search vs Semantic Search?
Almost any production RAG; the wins are essentially free once your vector DB supports it. Semantic Search applies when you are focused on agents & tools.
Are Hybrid Search and Semantic Search the same thing?
No. Hybrid Search is agents & tools; Semantic Search is agents & tools. They are related but address different parts of the AI stack.