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    BM25 vs OpenAI Embeddings: Why a 1994 Ranker Still Wins

    81
    Retrieval & Search Research
    Mixpeek Team
    July 14, 2026

    Summary

    A keyword ranking function from 1994 beat OpenAI's best embedding models on standard retrieval benchmarks. The video explains how BM25 works, where dense embeddings genuinely win, and why production search stacks run both stages rather than picking a side.

    bm25embeddingsopenairankinghybrid-search

    About this video

    A keyword ranking function from 1994 beat OpenAI's best embedding models on standard retrieval benchmarks. The video explains how BM25 works, where dense embeddings genuinely win, and why production search stacks run both stages rather than picking a side.

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