landing_page/qdrant-landing/content/course/multi-vector-search/module-3/pooling-techniques.md

title, description, weight

title	description	weight
Pooling Techniques	Reduce the number of vectors per document using row/column pooling and hierarchical token pooling strategies.	3

{{< date >}} Module 3 {{< /date >}}

Pooling Techniques

While quantization reduces the size of each vector, pooling reduces the number of vectors per document. By intelligently combining token embeddings, you can achieve significant memory savings while preserving retrieval quality.

Pooling is particularly effective when combined with quantization for maximum memory efficiency.

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Now let's tackle the indexing challenge with MUVERA, enabling fast approximate search for multi-vector representations.