Qwen Text Embedding v3 API

High-quality text embedding model with support for custom dimensions (512-1024) and over 50 languages. Suitable for semantic search, recommendation systems, and text analysis.

Input price: $0.07per 1M tokens
Model type: Embeddings
Released: Dec 13, 2025

Qwen Text Embedding v3 overview

Qwen Text Embedding v3 by Alibaba Cloud

Alibaba's multilingual embedding model, configurable dimensions (512–1024) across 50+ languages for semantic search and retrieval.

Qwen Text Embedding v3 specs

Model ID: alibaba/qwen-text-embedding-v3
Developer: Alibaba Cloud
Input: Text
Endpoint: POST https://api.aimlapi.com/v1/embeddings

What Is Qwen Text Embedding v3 API?

Qwen Text Embedding v3 is Alibaba Cloud’s embedding model for turning text into vectors for retrieval and related semantic tasks.

The available documentation and model pages indicate it is a multilingual embedding model with configurable output dimensions and support for text-search workflows.

Technical Reference

Developer	Alibaba Cloud
Model ID	alibaba/qwen-text-embedding-v3
Release Date	December 12, 2025
Context Window	8,192 tokens (~8K)
Modalities	Text → Embedding

What Qwen Text Embedding v3 Brings to the Table

Multilingual coverage
Alibaba Cloud documents Qwen Text Embedding v3 as supporting 50+ major languages, including Chinese, English, Spanish, French, Portuguese, Indonesian, Japanese, Korean, German, and Russian.

Configurable embedding dimensions
The model supports output dimensions of 1,024 by default, with additional dimension options listed in Alibaba Cloud documentation such as 768, 512, 256, 128, and 64.

Long input support
The documentation lists a maximum batch token limit of 8,192 for the embedding service.

Embedding service on Model Studio
Alibaba Cloud exposes the model through its Model Studio embedding offering, which is presented as an embedding API for vector generation.

Where Qwen Text Embedding v3 Makes the Most Sense

Semantic retrieval
The model is suitable for transforming queries and documents into embeddings for search and retrieval workflows.

Text classification
Alibaba Cloud and related Qwen materials describe embedding models like this one as useful for classification tasks.

RAG pipelines
The model is positioned for retrieval-augmented generation workflows where document vectors are used to fetch relevant context.

Cross-lingual search
Its multilingual support makes it appropriate for queries and documents in different languages.

Qwen Text Embedding v3 vs the Alternatives

Qwen3 embedding models
Qwen’s later embedding series is described as a family of text embedding and reranking models with 0.6B, 4B, and 8B variants.

OpenAI and Gemini embedding APIs
A third-party comparison article describes Qwen as a strong alternative to existing embedding solutions such as Gemini Embedding and OpenAI’s embedding APIs.

Sources: https://www.alibabacloud.com/blog/mastering-text-embedding-and-reranker-with-qwen3_602308 · https://www.alibabacloud.com/blog/602349 · https://docs.aimlapi.com/api-references/embedding-models/alibaba-cloud/qwen-text-embedding-v3

Use cases

Semantic search is a documented use case for Qwen Text Embedding v3, since the model converts text into vectors for similarity-based retrieval.

Recommendation systems are another documented use case, including web search and recommendation applications, where embeddings support downstream matching and ranking.

Clustering is also explicitly listed, with embeddings used to group similar texts or documents together.

Classification is documented as a supported downstream task, including text categorization and related analysis workflows.

Qwen Text Embedding v3 API pricing

Qwen Text Embedding v3 pricing in US dollars
Usage	Price	Unit
Input	$0.07	1M tokens

Prices from the AI/ML API price list, checked on Nov 4, 2026.

How to use the Qwen Text Embedding v3 API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/embeddings' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "alibaba/qwen-text-embedding-v3",
  "input": "The quick brown fox jumps over the lazy dog."
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "alibaba/qwen-text-embedding-v3",
    "input": "The quick brown fox jumps over the lazy dog."
}

response = requests.post("https://api.aimlapi.com/v1/embeddings", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/embeddings", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "alibaba/qwen-text-embedding-v3",
    "input": "The quick brown fox jumps over the lazy dog."
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

Qwen Text Embedding v3 FAQ

What is the context window of Qwen Text Embedding v3?

Qwen Text Embedding v3 has a 8,192 tokens context window.

What inputs and outputs does Qwen Text Embedding v3 support?

Qwen Text Embedding v3 takes text as input and returns embedding.

When was Qwen Text Embedding v3 released?

Qwen Text Embedding v3 became available on December 13, 2025.

How much does Qwen Text Embedding v3 cost?

Qwen Text Embedding v3 costs $0.07 per 1M input tokens on AI/ML API, billed as you go with no subscription.

Who created Qwen Text Embedding v3?

Qwen Text Embedding v3 was built by Alibaba Cloud.

How do I call Qwen Text Embedding v3 on AI/ML API?

Send a request to https://api.aimlapi.com/v1/embeddings with alibaba/qwen-text-embedding-v3 as the model id.

Is Qwen Text Embedding v3 available through a single API key?

Yes. Qwen Text Embedding v3 is served through AI/ML API, so the same key and endpoint format used for other models applies.

How many languages does Qwen Text Embedding v3 support?

It supports over 50 languages.

What embedding dimensions can Qwen Text Embedding v3 produce?

It supports custom output dimensions ranging from 512 to 1024.

What is the model identifier for Qwen Text Embedding v3?

Its model ID is alibaba/qwen-text-embedding-v3.

Start building with Qwen Text Embedding v3

Get API key

Qwen Text Embedding v3 API

alibaba/qwen-text-embedding-v3

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/embeddings' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "alibaba/qwen-text-embedding-v3",
  "input": "The quick brown fox jumps over the lazy dog."
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "alibaba/qwen-text-embedding-v3",
    "input": "The quick brown fox jumps over the lazy dog."
}

response = requests.post("https://api.aimlapi.com/v1/embeddings", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/embeddings", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "alibaba/qwen-text-embedding-v3",
    "input": "The quick brown fox jumps over the lazy dog."
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

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Qwen Text Embedding v3 API

Qwen Text Embedding v3 overview

Qwen Text Embedding v3 by Alibaba Cloud

Qwen Text Embedding v3 specs

What Is Qwen Text Embedding v3 API?

Technical Reference

What Qwen Text Embedding v3 Brings to the Table

Where Qwen Text Embedding v3 Makes the Most Sense

Qwen Text Embedding v3 vs the Alternatives

Use cases

Qwen Text Embedding v3 API pricing

How to use the Qwen Text Embedding v3 API

Build with your agent

1Get your API key

2Make your first request

Qwen Text Embedding v3 FAQ

Start building with Qwen Text Embedding v3

Qwen Text Embedding v3 API

Build with your agent

1Get your API key

2Make your first request

Qwen Text Embedding v3 API

Qwen Text Embedding v3 overview

Qwen Text Embedding v3 by Alibaba Cloud

Qwen Text Embedding v3 specs

What Is Qwen Text Embedding v3 API?

Technical Reference

What Qwen Text Embedding v3 Brings to the Table

Where Qwen Text Embedding v3 Makes the Most Sense

Qwen Text Embedding v3 vs the Alternatives

Use cases

Qwen Text Embedding v3 API pricing

How to use the Qwen Text Embedding v3 API

Build with your agent

1Get your API key

2Make your first request

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