Qwen3 Embedding 4B · aihubmix

Name: Qwen3 Embedding 4B
Brand: Qwen
Price: 0.068 USD
Availability: InStock

The Qwen3 Embedding model series is the latest proprietary model family from Qwen, specifically designed for text embedding and ranking tasks. Based on the dense base models of the Qwen3 series, it offers comprehensive text embedding and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the excellent multilingual capabilities, long-text understanding, and reasoning skills of its base models. The Qwen3 Embedding series demonstrates significant advancements in various text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bilingual text mining.

Base model All models on this base All models of the provider to the provider

Input, $/1M $0.068

Output, $/1M $0.068

Context —

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Last checked 04.11.2026 12:00:14 UTC

Source provider's page

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API

OpenAI-compatible API: the official OpenAI SDKs work with this base URL. Replace YOUR_API_KEY with your key from the provider.

API base URL	`https://aihubmix.com/api/v1`
Endpoint	`https://aihubmix.com/api/v1/embeddings`
Model id	`qwen3-embedding-4b`

curl

curl https://aihubmix.com/api/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen3-embedding-4b", "input": ["first text", "second text"]}'

Python

import requests

r = requests.post(
    "https://aihubmix.com/api/v1/embeddings",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
      "model": "qwen3-embedding-4b",
      "input": [
        "first text",
        "second text"
      ]
    },
)
print(r.json())

JavaScript

const r = await fetch("https://aihubmix.com/api/v1/embeddings", {
  method: "POST",
  headers: {Authorization: "Bearer YOUR_API_KEY", "Content-Type": "application/json"},
  body: JSON.stringify({
    "model": "qwen3-embedding-4b",
    "input": [
      "first text",
      "second text"
    ]
  }),
});
console.log(await r.json());

Request (JSON)

{
  "model": "qwen3-embedding-4b",
  "input": [
    "first text",
    "second text"
  ]
}

Response (JSON)

{
  "object": "list",
  "model": "qwen3-embedding-4b",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0.0123,
        -0.0456,
        "..."
      ]
    }
  ],
  "usage": {
    "prompt_tokens": 6,
    "total_tokens": 6
  }
}

The address is taken from the provider's model list; check it against the provider's documentation.

Provider's API documentation

Source: AI Rate Card, https://airatecard.com/en/c/offer%3Aaihubmix%7Cqwen3-embedding-4b, prices checked 2026-11-04; seller's page: https://aihubmix.com

Technical details

ID: offer:aihubmix|qwen3-embedding-4b