Qwen-Max

Alibaba Qwen chattool_usecode

API ID: qwen/qwen-max-2025-01-25

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Input Price
$1.04
/1M tokens
Output Price
$4.16
/1M tokens

About Qwen-Max

Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown.

💰
Price Ranking
#1060 lowest price among 1240 Chat models

Model Specifications

Context Length
33k
Max Output
8k
Release Date
2025-02-01
Capabilities
chat tool_use code
Input Modalities
text
Output Modalities
text

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
$1.72
/month
50 conversations/day, ~500 tokens each
Code Copilot
$14.98
/month
200 completions/day, ~1k tokens each
Customer Service Bot
$53.04
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$73.32
/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
Qwen-Max Current Free Free 33k 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 Qwen-Max 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/qwen-max-2025-01-25",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)

Resources

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