models/BAAI/BGE Reranker Base

BGE Reranker Base

rerank

Paired with bge-m3 for two-stage retrieval: recall with embeddings, precision with this reranker.

slug · baai/bge-reranker-baseprovider · BAAIfamily · BGE

Quickstart

POST /v1/chat/completions  model: "baai/bge-reranker-base"

Capabilities

Strengths

  • Strong cross-encoder reranking
  • Open-weight
  • Near-free

Use cases

RAG rerankingSearch result reordering

Pricing

Per request$0.0000
Open-weight
You pay pass-through · 5% applied at credit top-up, not per-call.
Try in playground →CompareAPI referenceSee usage ranking →

Collections

More embedding models →More from BAAIFrontier models →Free-tier models →
API schema

Call BGE Reranker Base from any OpenAI SDK

POST https://api.aigateway.sh/v1/embeddings·Content-Type: application/json·Auth: Bearer sk-aig-...

Request body

json
{
  "model": "baai/bge-reranker-base",
  "input": "Text to embed, or an array of strings for batch."
}

Response

json
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0123, -0.0456, 0.0789, /* ... */]
    }
  ],
  "model": "baai/bge-reranker-base",
  "usage": { "prompt_tokens": 5, "total_tokens": 5 }
}

Quickstart

from openai import OpenAI
client = OpenAI(base_url="https://api.aigateway.sh/v1", api_key="sk-aig-...")

r = client.embeddings.create(model="baai/bge-reranker-base", input="hello world")
print(r.data[0].embedding[:5])

Errors

401authentication_errorInvalid or missing API key
402insufficient_creditsWallet empty (PAYG only)
404not_foundUnknown model or endpoint
429rate_limit_errorOver per-minute limit — see Retry-After header
500server_errorUpstream provider failed (retryable)
503service_unavailableUpstream saturated (retryable)
Full docs →API reference →OpenAPI spec →llms.txt →