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

title, description, isLesson, weight

title	description	isLesson	weight
Module 3: Scalability and Optimization	Address scalability challenges in multi-vector search. Learn optimization techniques including quantization, pooling, MUVERA, and multi-stage retrieval.	true	40

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

Scalability and Optimization

Tackle the memory and performance challenges of production-scale multi-vector search.

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Today's path

1. Memory Usage Implications and Solutions
2. Vector Quantization Techniques (Scalar, Binary, +1.5/2-bit)
3. Pooling Techniques (Row/Column, Hierarchical Token Pooling)
4. MUVERA for HNSW Compatibility
5. Multi-Stage Retrieval with Universal Query API
6. Evaluating Search Pipelines (Cost vs. Latency)

You'll master the optimization strategies needed to deploy multi-vector search at scale.