Guides
From “what is a reranker?” to hybrid retrieval pipelines and evaluation — pick a starting point or read straight through.
Read these in order
Five guides that build on each other, from what a reranker does to measuring one on your own data.
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What is a reranker?
Two-stage retrieval, why order matters, when reranking pays off.
Fundamentals~7 min -
Cross-encoder vs bi-encoder
Speed vs accuracy — and why production stacks use both.
Architecture~8 min -
How to add reranking to RAG
Retrieve wide, rerank tight — with Python, LangChain, and latency tips.
Practical~10 min -
Hybrid retrieval + rerank
Combine BM25 and vector search, then let the reranker fix the merge.
Production~9 min -
How to evaluate rerankers
NDCG, MRR, labelled queries, and regression tests for your domain.
Evaluation~8 min
Already have a specific question?
Go straight to the page for the job in front of you.
Choose by scenario
RAG vs support vs legal vs code — which model fits your use case.
Reranking in mainland China
Alibaba Cloud, SiliconFlow or your own server — prices in yuan, Chinese scores, downloading weights.
Reranking didn't help
Seven reasons you see no lift — recall, pool size, truncation — and how to tell which one you have.
Rerank cost calculator
Per-search or per-token? Which rerank API is cheaper at your volume.
Self-host a reranker
sentence-transformers, GPU sizing, and a minimal FastAPI service.
Rerank on a vector database
Wiring a rerank stage onto pgvector, Qdrant or Elasticsearch, with code.
Late-interaction (ColBERT)
When ColBERT beats bi-encoders and when you still need cross-encoder rerank.
Instruction-following rerank
Task instructions that change what “relevant” means — vs plain cross-encoders.
Live in-browser demo
Watch a cross-encoder reorder passages — bi-encoder proxy included.