# efficiency

> Browse 4 items tagged with efficiency.

## Items

- [MUVERA](https://vectordb.ever.works/de/items/muvera) — Multi-Vector Retrieval Algorithm that reduces multi-vector similarity search to single-vector similarity search via Fixed Dimensional Encodings. Achieves 10% improved recall with 90% lower latency compared to existing approaches.
- [XTR](https://vectordb.ever.works/de/items/xtr) — ConteXtualized Token Retriever that introduces a novel objective function encouraging the model to retrieve the most important document tokens first. Enables ranking 4,000x cheaper than ColBERT's refinement stage with state-of-the-art performance.
- [CSRv2](https://vectordb.ever.works/de/items/csrv2) — Contrastive Sparse Representation learning approach for ultra-sparse embeddings that achieves 7x speedup over Matryoshka Representation Learning with 300x improvements in compute and memory efficiency.
- [Intelligence Per Watt](https://vectordb.ever.works/de/items/intelligence-per-watt) — Research metric from Stanford measuring AI model efficiency, showing local language models improved 5.3× from 2023 to 2025, handling 88.7% of single-turn queries.

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_Canonical page: https://vectordb.ever.works/de/tags/efficiency_