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Qdrant tests Perplexity’s PDF embeddings: 21× smaller compressed vectors, with originals still stored

Qdrant tested Perplexity’s new visual document embeddings on 11,609 pages across four ViDoRe v3 datasets. The models search pages as images, so tables and layout can stay intact. Their result: 1-bit TurboQuant reduced the compressed vectors from 856 KB to 40 KB per page while retaining 96.5% of the…

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  1. 2026-10-17 02:52 · r/ArtificialInteligence
    Qdrant tests Perplexity’s PDF embeddings: 21× smaller compressed vectors, with originals still stored

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