Comparison
BM25 vs Hybrid Search
BM25 and Hybrid Search are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for BM25
BM25 comes up when the question is fundamentally about agents & tools.
A codebase search where BM25 finds every file containing the exact function name; vector alone often missed them.
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.
Frequently asked
What is the difference between BM25 and Hybrid Search?
BM25: BM25 is the classical keyword-based ranking algorithm: a refined TF-IDF that scores documents by query-term frequency, document length, and corpus-wide rarity. The keyword side of hybrid 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.
When should I use BM25 vs Hybrid Search?
BM25 is the right concept when you are focused on agents & tools. Almost any production RAG; the wins are essentially free once your vector DB supports it.
Are BM25 and Hybrid Search the same thing?
No. BM25 is agents & tools; Hybrid Search is agents & tools. They are related but address different parts of the AI stack.