Qwen-Plus

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ReasoningText Generation

Overview

ReasoningText Generation

Qwen-Plus is an enhanced version of the Qwen ultra-large language model that supports multiple input languages such as Chinese and English. Compared to previous versions, it shows significant improvements in both Chinese and English code generation, logical reasoning, and multilingual abilities. The response style has been greatly adjusted to align with human preferences, with noticeable enhancements in the level of detail and clarity of responses. Specialized improvements have been made in creative writing, adherence to JSON formatting, and role-playing abilities.

Input

Text

Output

Text

Features

Prefix Completion

Function Calling

Cache

Structured Outputs

Batches

Web Search

Pricing

Input
$0.4Per 1M tokens
Output
$1.2Per 1M tokens
Input(Thinking)
$0.4Per 1M tokens
Output(Thinking)
$4Per 1M tokens
Input(Implicit Cache)
$0.08Per 1M tokens
Input(Thinking Implicit Cache)
$0.08Per 1M tokens
Thinking Output(Batch File)
$2Per 1M tokens
Input(Batch File)
$0.2Per 1M tokens
Output(Batch File)
$0.6Per 1M tokens
Input(Thinking Batch File)
$0.2Per 1M tokens
Explicit Cache Creation
$0.5Per 1M tokens
Explicit Cache Read
$0.04Per 1M tokens
Explicit Cache Creation(Thinking)
$0.5Per 1M tokens
Explicit Cache Read(Thinking)
$0.04Per 1M tokens

Input
$0.4Per 1M tokens
Output
$1.2Per 1M tokens
Input(Thinking)
$0.4Per 1M tokens
Output(Thinking)
$4Per 1M tokens
Input(Implicit Cache)
$0.08Per 1M tokens
Input(Thinking Implicit Cache)
$0.08Per 1M tokens
Thinking Output(Batch File)
$2Per 1M tokens
Input(Batch File)
$0.2Per 1M tokens
Output(Batch File)
$0.6Per 1M tokens
Input(Thinking Batch File)
$0.2Per 1M tokens
Explicit Cache Creation
$0.5Per 1M tokens
Explicit Cache Read
$0.04Per 1M tokens
Explicit Cache Creation(Thinking)
$0.5Per 1M tokens
Explicit Cache Read(Thinking)
$0.04Per 1M tokens

Context

Max Input

995.90K

Max Output

32.76K

Rate Limits

RPMRequests Per Minute
600
TPMTokens Per Minute
1M

API Reference

Get API Key

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import os
from dashscope import Generation
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Who are you?"},
]
response = Generation.call(
    # 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"),
    model="qwen-plus",
    messages=messages,
    result_format="message",
    # Enable deep thinking
    enable_thinking=True,
)

if response.status_code == 200:
    # Print thinking process
    print("=" * 20 + "Thinking process" + "=" * 20)
    print(response.output.choices[0].message.reasoning_content)
    
    # Print response
    print("=" * 20 + "Full response" + "=" * 20)
    print(response.output.choices[0].message.content)
else:
    print(f"HTTP return code: {response.status_code}")
    print(f"Error code: {response.code}")
    print(f"Error message: {response.message}")