Qwen3 Embedding 4B

About Qwen3 Embedding 4B

Qwen3 Embedding is Alibaba's text embedding model series, designed for semantic search and retrieval applications. The models generate high-quality vector representations that capture semantic meaning effectively. Available in 0.6B, 4B, and 8B parameter versions, they offer flexibility between efficiency and capability. Qwen3 Embedding achieves strong performance on embedding benchmarks with particular strength in Chinese language content. The models support multilingual text and integrate well with RAG pipelines. For developers building search and retrieval systems with multilingual requirements, Qwen3 Embedding provides capable semantic understanding.

Model Specifications

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

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🚀 Quick Start

Get started with Qwen3 Embedding 4B API

from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="qwen/qwen3-embedding-4b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)

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