# dimensions

> Browse 2 items tagged with dimensions.

## Items

- [Embedding Dimension Selection](https://vectordb.ever.works/items/embedding-dimension-selection) — Guide to choosing optimal embedding dimensions balancing accuracy, storage costs, and computational requirements, covering Matryoshka embeddings and dimension reduction techniques.
- [Embedding Dimensionality](https://vectordb.ever.works/items/embedding-dimensionality) — The size of vector embeddings, typically ranging from 384 to 4096 dimensions. Higher dimensions capture more information but increase storage, compute, and latency costs.

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_Canonical page: https://vectordb.ever.works/tags/dimensions_