models/Alibaba/Qwen3 Rerank
Alibaba

Qwen3 Rerank

rerank
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MODALITIES
embedding
INPUT
$0.100 /1M
OUTPUT
$0 /1M

Qwen3 Rerank (alibaba/qwen3-rerank) is a rerank model from Alibaba. Context window: tokens; max output . Pricing via AIgateway: input $0.100/M tokens, output $0/M tokens. Call it via https://api.aigateway.sh/v1/rerank — set model="alibaba/qwen3-rerank".

model · alibaba/qwen3-rerank

Use this model

model: alibaba/qwen3-rerank
curl https://api.aigateway.sh/v1/rerank \
  -H "Authorization: Bearer $AIGATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"alibaba/qwen3-rerank","query":"weather","documents":["sun is bright","mars is red"]}'

Capabilities

Strengths

  • Relevance scoring
  • Two-stage retrieval

Pricing

Input$0.100 / 1M tokens
Output$0 / 1M tokens
You pay pass-through pricing.
See API example →CompareAPI referenceSee usage ranking →

Collections

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

Call Qwen3 Rerank from any OpenAI SDK

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

Request body

json
{
  "model": "alibaba/qwen3-rerank",
  "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": "alibaba/qwen3-rerank",
  "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="alibaba/qwen3-rerank", 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 →

Frequently asked questions

What is Qwen3 Rerank?
undefined It is a rerank model from Alibaba, accessible via AIgateway's OpenAI-compatible API at slug alibaba/qwen3-rerank.
How much does Qwen3 Rerank cost via AIgateway?
Input costs $0.100 per 1M tokens; output costs $0.000 per 1M tokens, billed pass-through.
How do I call Qwen3 Rerank from my code?
Point the OpenAI SDK at https://api.aigateway.sh/v1 with your AIgateway key and set model to "alibaba/qwen3-rerank". The request and response shapes match OpenAI exactly.
Does Qwen3 Rerank support streaming, tool calling, vision, and JSON mode?
Streaming — no. Tool calling — no. Vision — no. JSON mode — no. Prompt caching — no.
What are the best use cases for Qwen3 Rerank?
Key strengths: Relevance scoring; Two-stage retrieval.
Can I bring my own Alibaba API key (BYOK)?
Yes. Attach a Alibaba key in your AIgateway dashboard and this model flips to pass-through — you pay Alibaba directly and AIgateway adds no platform fee on those calls.