Reranker
A second-stage model that reorders retrieved chunks for precision.
/ quick answer
A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency. A second-stage model that reorders retrieved chunks for precision.
/ frequently asked
What is Reranker?
A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency.
What is an example of Reranker?
Retriever returns 50 candidates; the reranker keeps the top 5 with the strongest semantic match.
Why does Reranker matter?
A second-stage model that reorders retrieved chunks for precision.
What should I learn after Reranker?
Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Contextual Compression
Contextual compression is a technique used to reduce the size of the input context for a Large Language Model (LLM) while retaining its most relevant information, typically by summarizing or filtering.
- →Retrieval
Selecting the most relevant chunks for a query before generation.
- →RAG (Retrieval-Augmented Generation)
Inject external knowledge into an LLM at query time.
- →Agentic RAG
RAG where an agent decides what to retrieve, when, and from which source — instead of a single static query.
Related workflows
Turn this into a repeatable process.
- →Build an Internal Knowledge Bot
Ship a Slack bot that answers questions from your company docs.
- →How to Create a Website with AI
Go from idea to a live, custom-domain website in one afternoon using AI builders.
- →How to Build an AI Content System
A repeatable pipeline that turns one input into publish-ready content across every channel.
- →How to Start a Niche Website with AI
Pick a niche, validate demand, build the site, and publish ranking content using AI end-to-end.
Related tool stacks
The tools that run it in production.
- →RAG Starter Stack
Minimum viable stack to ship a production RAG chatbot.
- →LLM Context Management Stack
A technology stack for effectively managing and optimizing the context provided to large language models, ensuring efficient, relevant, and cost-effective operations.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
Comparisons & alternatives
Pick between the options.
- →ChatGPT vs Claude
Two leading conversational AI assistants compared across reasoning, writing, coding, and pricing.
- →Lovable vs Bolt
Two AI app builders compared on speed, backend, deployment, and production readiness.
- →OpenAI API vs Anthropic API
Choosing between the two leading LLM API providers for production apps.
- →Lovable vs Cursor
Prompt-to-app builder vs AI-assisted code editor — which one should you reach for?