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Reranking Models: The Cheapest RAG Quality Upgrade

Last year I took over a support chatbot for a client with about 40,000 help center and internal wiki chunks in a vector database. Retrieval was pure dense vector search.

  • Reranking improves RAG accuracy from 61% to 84% for $40/month
  • Bi-encoders excel at recall, not precision, causing wrong chunk ranking
  • Hybrid retrieval with BM25 and dense vectors handles exact string matches better

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