Qwen3 Reranker 8B

Origin

qwen/qwen3-reranker-8b

Qwen3 Reranker 8B is a text reranking model from Alibaba Cloud built on the Qwen3 architecture. It evaluates query-document pairs to produce relevance scores for use in retrieval and RAG...

Pricing

Billed at actual usage

Billing follows the provider's own reported cost. The unit prices here are for reference; a model marked "billed at actual usage" has no reliable pre-call price, so your usage page is the record of what you paid.

Call it

Rerank models are served on POST /v1/rerank. Send a query and a list of documents and get them back ranked by relevance; top_n limits how many come back. Billing follows the provider's reported cost.

curl https://macdecloud.com/v1/rerank \
  -H "Authorization: Bearer dcld-sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen/qwen3-reranker-8b","query":"What is the capital of France?","documents":["Paris is the capital of France.","Berlin is the capital of Germany."],"top_n":1}'

Python

The OpenAI SDK has no rerank method; POST with httpx, which the SDK already depends on.

import httpx

resp = httpx.post(
    "https://macdecloud.com/v1/rerank",
    headers={"Authorization": "Bearer dcld-sk-..."},
    json={
        "model": "qwen/qwen3-reranker-8b",
        "query": "What is the capital of France?",
        "documents": ["Paris is the capital of France.", "Berlin is the capital of Germany."],
        "top_n": 1,
    },
)
for r in resp.json()["results"]:
    print(r["index"], r["relevance_score"])