Which reranker fits your scenario?

Decision guide · ~8 min read ·

Rerankers are not one-size-fits-all. The right choice depends on language coverage, latency budget, data sensitivity, and whether your queries look more like support tickets, legal clauses, code search, or RAG chunks.

Scenario matrix

ScenarioTypical challengeStarting recommendationRun where
RAG pipeline Noisy vector recall, need top-5 precision bge-reranker-v2-m3 (self-host) or Cohere Rerank (API) Your GPU / hosted API
Customer support Many similar FAQ lines, fast response jina-reranker tiny or Cohere free tier API or browser demo
Legal / contracts Subtle wording, distractors share vocabulary mxbai-rerank-large or Voyage legal-tuned Self-host / API
Code & API docs Exact identifiers, syntax matters Voyage code or hybrid BM25 + bge Hybrid retrieve + rerank

RAG & knowledge bases

Retrieve 50–100 chunks, rerank to 5–10, then prompt. Multilingual knowledge bases favour bge-v2-m3 or Cohere v3.5. English-only stacks with tight quality targets often pick mxbai-large. See rerank for RAG and hybrid retrieval when lexical matches matter.

Rule of thumb: if bi-encoder recall is already good, a mid-size reranker is enough. If recall is messy, fix retrieval width first.

Customer support

Queries are short, passages are FAQ-sized, and latency dominates UX. A tiny cross-encoder (Jina tiny, ms-marco MiniLM) often suffices — you are choosing among a handful of similar answers, not reading 100-page PDFs. Try the Customer support preset in our demo.

Distractors share vocabulary (“termination”, “notice period”, “breach”). Bi-encoders confuse them; cross-encoders separate nuance. Budget extra latency for a larger model and keep passages to single clauses. Demo preset: Legal clause.

Code & technical docs

Vector search alone misses exact function names; BM25 alone misses paraphrased “how do I…” questions. Use hybrid retrieval, then rerank. Domain rerankers (Voyage code) help; otherwise bge-base + good chunking works. Demo presets: Technical docs and Code search.

Try it in the demo

Each scenario below maps to a built-in preset — load it, hit Rerank, and watch the bi-encoder proxy column mis-order before the cross-encoder fixes it.

Still deciding?

Compare all five model families side by side, then jump into the demo with one click.

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