Qwen-Plus

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Overview

A balanced model in the Qwen series, with inference effectiveness and speed between Qwen-Max and Qwen-Turbo, making it suitable for moderately complex tasks. Compared to Qwen-Plus-2025-0112, there is a comprehensive upgrade in both Chinese and English capabilities. Notably, there are significant improvements in coding ability, logical reasoning, and multilingual support. The response style has been significantly adjusted to align with human preferences, especially for objective queries such as mathematics, logical reasoning, and knowledge-based questions—both the level of detail in responses and the clarity of formatting have improved noticeably. Additionally, targeted enhancements have been made in creative writing, JSON format compliance, and role-playing abilities. This version is expected to be maintained until one month before the next snapshot release.

Input

Text

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

Input
$0.4Per 1M tokens
Output
$1.2Per 1M tokens

Rate Limits & Context

Max Input
128K
Max Output
8K
Context
131K
TPMTokens Per Minute
100K
RPMRequests Per Minute
60

API Reference

Call API

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import os
from openai import OpenAI

client = OpenAI(
    # If the environment variable is not set, replace it with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://ap-southeast-1.maas.qwencloudapi.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
    model="qwen-plus-2025-01-25",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who are you?"},
    ],
    stream=True
)
for chunk in completion:
    print(chunk.choices[0].delta.content, end="", flush=True)