Qwen3 Embedding 8B

Alibaba Qwen chattool_usecode

API ID: qwen/qwen3-embedding-8b

Input Price
$0.01
/1M tokens
Output Price
Free
/1M tokens

About Qwen3 Embedding 8B

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.

๐Ÿ’ฐ
Price Ranking
#555 lowest price among 950 Chat models

Model Specifications

Context Length
32k
Max Output
32k
Release Date
2025-10-28
Capabilities
chat tool_use code
Input Modalities
text
Output Modalities
embeddings

Best For

  • Code generation, debugging, code review, refactoring
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.00
/month
50 conversations/day, ~500 tokens each
Code Copilot
$0.05
/month
200 completions/day, ~1k tokens each
Customer Service Bot
$0.15
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$0.23
/month
500 analyses/day, ~2k tokens each

Alibaba Qwen Model Lineup

Compare all models from Alibaba Qwen to find the best fit

Model Input Output Context Capabilities
Qwen3 Embedding 8B Current Free Free 32k chat tool_use code
Qwen2.5-VL 7B Instruct Free Free 33k chat vision tool_use
Qwen3 Embedding 0.6B Free Free 8k chat code
Qwen3 Embedding 0.6B Free Free 8k chat code
Qwen2.5 VL 3B Instruct Free Free 64k chat vision code
Qwen2.5 VL 3B Instruct Free Free 64k chat vision code

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Other bge-large-en-v1.5
Input: $0.01
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๐Ÿš€ Quick Start

Get started with Qwen3 Embedding 8B API

OpenAI-compatible SDK
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-8b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)