Qwen3 Embedding 8B

Alibaba Qwen chattool_usecode

API ID: qwen/qwen3-embedding-8b

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

About Qwen3 Embedding 8B

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.

📊
Price Ranking
#576 lowest price among 1240 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)

💰 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
Calculate Your Custom Usage

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
View All Alibaba Qwen Models →

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🚀 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)

Resources

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