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Mem0 rerankers rescore vector search hits so your agents surface the most relevant memories. Use this hub to decide when reranking helps, configure a provider, and fine-tune performance.
Reranking trades extra latency for better precision. Start once you have baseline search working and measure before/after relevance.

Supported Rerankers

https://mintcdn.com/mem0/QK-8_hblyHgAr7vt/images/provider-icons/cohere.svg?fit=max&auto=format&n=QK-8_hblyHgAr7vt&q=85&s=343843b1c9c9268bdb2cf09fba221266

Cohere

Sentence Transformers

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Hugging Face

LLM Reranker

https://mintcdn.com/mem0/QK-8_hblyHgAr7vt/images/provider-icons/zeroentropy.svg?fit=max&auto=format&n=QK-8_hblyHgAr7vt&q=85&s=8a48819985d4366a8f619384669052b7

Zero Entropy

Reranking Workflow

Understand Reranking

Configure Providers

Optimize Performance

Custom Prompts

Zero Entropy Guide

Sentence Transformers

Picking the Right Reranker

  • API-first when you need top quality and can absorb request costs (Cohere, Zero Entropy).
  • Self-hosted for privacy-sensitive deployments that must stay on your hardware (Sentence Transformer, Hugging Face).
  • LLM-driven when you need bespoke scoring logic or complex prompts.
  • Hybrid by enabling reranking only on premium journeys to control spend.

Implementation Checklist

  1. Confirm baseline search KPIs so you can measure uplift.
  2. Select a provider and add the reranker block to your config.
  3. Test latency impact with production-like query batches.
  4. Decide whether to enable reranking globally or per-search via the rerank flag.

Set Up Reranking

Example: Reranker Search