How to Use Qwen 2.5: A Comprehensive Guide

Qwen 2.5 has emerged as a formidable player in the rapidly evolving landscape of artificial intelligence, , offering advanced capabilities in language

AnnaAI model and API research team

Updated Sep 3, 2026 7 min read

How to Use Qwen 2.5: A Comprehensive Guide

Use this pattern

Make the first API call.

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_COMETAPI_KEY",
    base_url="https://api.cometapi.com/v1",
)

response = client.chat.completions.create(
    model="gpt-5-mini",
    messages=[{"role": "user", "content": "Build this workflow."}],
)

print(response.choices[0].message.content)

Qwen 2.5 has emerged as a formidable player in the rapidly evolving landscape of artificial intelligence, , offering advanced capabilities in language understanding, reasoning, and code generation. Developed by Alibaba Cloud, this model is designed to rival industry leaders, providing versatile applications across various domains. This article delves into the intricacies of Qwen 2.5, exploring its features, usage, and how it compares to other models like DeepSeek R1.

Qwen 2.5

What Is Qwen 2.5?

Qwen 2.5 is a general-purpose AI language model developed by Alibaba Cloud. It excels in language understanding, reasoning, and code generation, positioning itself as a versatile powerhouse in the AI industry. Unlike models focused solely on specific tasks, Qwen 2.5 offers state-of-the-art performance across various applications, from enterprise solutions to research and development. citeturn0search0

Key Features of Qwen 2.5

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Published on Mar 19, 2025

Last updated Sep 3, 2026

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Reviewed for clarity, source attribution and current API terminology.

How to Use Qwen 2.5: A Comprehensive Guide - CometAPI

pip install requests transformers torch

pip install transformers

import requests

API_KEY = "your_api_key"
URL = "https://api.alibabacloud.com/qwen"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

payload = {
    "prompt": "Explain quantum computing in simple terms.",
    "max_tokens": 500
}

response = requests.post(URL, headers=headers, json=payload)
print(response.json())

python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Qwen/Qwen-2.5"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "What are the applications of artificial intelligence?"
inputs = tokenizer(input_text, return_tensors="pt")

output = model.generate(**inputs, max_length=200)
print(tokenizer.decode(output, skip_special_tokens=True))

import requests
import json
url = "https://api.cometapi.com/v1/chat/completion:s"
payload = json.dumps({
"model": "qwen-max",
"messages": [
{
"role": "user"
"content": "Hello!"
],
"stream": False
headers = {
'Authorization': 'Bearer {{api-key}}',
'Content-Type': 'application/json'
response = requests.request("POST", url, headers=headers, data=payload)
print(response.text)

Feature	Qwen 2.5 72B	GPT-4o (OpenAI)	Gemini 1.5 (Google)	LLaMA 2 (Meta)
Model Type	General-purpose AI	Advanced reasoning and conversational AI	AI optimized for large-scale search and multimodal tasks	Research-oriented, fine-tunable AI
Training Data	18 trillion tokens	Proprietary (estimated trillions)	Proprietary (Google’s vast datasets)	Public datasets (fine-tunable)
Context Window	128,000 tokens	128,000 tokens	1 million tokens	4,096 tokens
Multimodal Support	Yes (text, images, audio)	Yes (text, images, audio, video)	Yes (text, images, audio, video, code)	No
Coding Abilities	Strong	Industry-leading	Strong	Moderate
Multilingual Support	29 languages	Over 50 languages	Over 100 languages	Limited
Open Source	Yes	No	No	Yes
Best Use Cases	AI assistants, coding, chatbot interactions, text processing

Read More

How to Use Qwen 2.5: A Comprehensive Guide

Make the first API call.

What Is Qwen 2.5?

Key Features of Qwen 2.5

Connect this article to the next decision.

How to Use Qwen 2.5?

How to Access Qwen 2.5?

Alibaba Cloud API:

Hugging Face Model Hub:

4. For Developers: API Access

Step-by-Step Guide: How to Use Qwen 2.5?

Step 1: Obtain API Credentials (for Cloud Access)

Step 2: Install Required Libraries

Step 3: Make an API Request (Cloud Usage)

Running Qwen 2.5 Locally

CometAPI intergrate qwen API

Leveraging Specialized Models

How Does Qwen 2.5 Compare to DeepSeek R1?

Performance Benchmarks

Specialization and Versatility

2. Qwen 2.5 vs. Other AI Models

Conclusion