Overview

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.

<Info> Reranking trades extra latency for better precision. Start once you have baseline search working and measure before/after relevance. </Info>

Supported Rerankers

<CardGroup cols={3}> <Card title="Cohere" icon="/images/provider-icons/cohere.svg" href="/components/rerankers/models/cohere" /> <Card title="Sentence Transformers" icon="vector-square" href="/components/rerankers/models/sentence_transformer" /> <Card title="Hugging Face" icon="/images/provider-icons/huggingface.svg" href="/components/rerankers/models/huggingface" /> <Card title="LLM Reranker" icon="wand-magic-sparkles" href="/components/rerankers/models/llm_reranker" /> <Card title="Zero Entropy" icon="/images/provider-icons/zeroentropy.svg" href="/components/rerankers/models/zero_entropy" /> </CardGroup> <Note> All five rerankers are available in both the Python and the [TypeScript](/open-source/features/reranker-search#typescript-sdk) self-hosted SDKs. Each provider page has a **TypeScript (self-hosted)** section with the camelCase config. </Note>

Reranking Workflow

<CardGroup cols={3}> <Card title="Understand Reranking" description="See how reranker-enhanced search changes your retrieval flow." icon="search" href="/open-source/features/reranker-search" /> <Card title="Configure Providers" description="Add reranker blocks to your memory configuration." icon="gear" href="/components/rerankers/config" /> <Card title="Optimize Performance" description="Balance relevance, latency, and cost with tuning tactics." icon="gauge" href="/components/rerankers/optimization" /> <Card title="Custom Prompts" description="Shape LLM-based reranking with tailored instructions." icon="code" href="/components/rerankers/custom-prompts" /> <Card title="Zero Entropy Guide" description="Adopt the managed neural reranker for production workloads." icon="sparkles" href="/components/rerankers/models/zero_entropy" /> <Card title="Sentence Transformers" description="Keep reranking on-device with cross-encoder models." icon="microchip" href="/components/rerankers/models/sentence_transformer" /> </CardGroup>

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.

<CardGroup cols={2}> <Card title="Set Up Reranking" description="Walk through the configuration fields and defaults." icon="gear" href="/components/rerankers/config" /> <Card title="Example: Reranker Search" description="Follow the feature guide to see reranking in action." icon="rocket" href="/open-source/features/reranker-search" /> </CardGroup>