Qwen 3 API

​The Qwen 3 API is an OpenAI-compatible interface developed by Alibaba Cloud, enabling developers to integrate advanced Qwen 3 large language models—available in both dense and mixture-of-experts (MoE) architectures—into their applications for tasks such as text generation, reasoning, and multilingual support.

Qwen 3 Overview

Key Features

• Hybrid Reasoning Capabilities: Qwen 3 integrates both conventional AI functions and advanced dynamic reasoning, enhancing adaptability and efficiency for developers.
• Scalability: The model family includes both dense (0.6B to 32B parameters) and sparse models (30B with 3B activated parameters, 235B with 22B activated parameters), catering to a wide range of applications.
• Extended Context Window: Most Qwen 3 models support a 128K token context window, facilitating the processing of lengthy documents and complex tasks.
• Multimodal Support: Qwen 3 models are capable of processing text, images, audio, and video inputs, making them suitable for diverse applications, including real-time voice interactions and visual data analysis.
• Open-Source Accessibility: All Qwen 3 models are licensed under the Apache 2.0 license and are available through platforms like Hugging Face and ModelScope.

Technical Architecture

Model Variants

Qwen 3 encompasses a range of models to address varying computational needs:

• Dense Models: Available in sizes of 0.6B, 1.7B, 4B, 8B, 14B, and 32B parameters.
• Sparse Models: Include a 30B model with 3B activated parameters and a 235B model with 22B activated parameters.

The architecture allows for efficient deployment across different hardware configurations, from mobile devices to high-performance servers.

Contextual Understanding

With a 128K token context window, Qwen 3 models can maintain coherence over extended interactions, making them adept at tasks requiring deep contextual understanding, such as long-form content generation and complex problem-solving.

Evolution of the Qwen Series

From Qwen to Qwen 3

The Qwen series has undergone significant evolution:​

• Qwen: Introduced as the base pretrained language models, demonstrating superior performance across various tasks.​
• Qwen-Chat: Chat models fine-tuned with human alignment techniques, showcasing advanced tool-use and planning capabilities.​
• Qwen2: Expanded the model suite with instruction-tuned language models, featuring parameter ranges from 0.5 to 72 billion. The flagship model, Qwen2-72B, exhibited remarkable performance across diverse benchmarks.
• Qwen2.5: Introduced models like Qwen2.5-Omni, capable of processing text, images, videos, and audio, and generating both text and audio outputs.
• Qwen 3: The latest iteration, incorporating hybrid reasoning capabilities and enhanced efficiency, marking a significant advancement in the series. ​

Benchmark Performance

Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.

• AIME25: Qwen3 scored 81.5 points, setting a new open source record.
• LiveCodeBench: Qwen3 scored over 70 points, even better than Grok3.
• ArenaHard: Qwen3 surpassed OpenAl-o1 and DeepSeek-FR1 with 95.6 points.

Code Example

Developers can interact with Qwen 3 models using the following Python code snippet:

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-3-14B")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-3-14B")

# Encode input prompt
input_text = "Explain the significance of hybrid reasoning in AI models."
input_ids = tokenizer.encode(input_text, return_tensors="pt")

# Generate response
output = model.generate(input_ids, max_length=200)
response = tokenizer.decode(output[0], skip_special_tokens=True)

print(response)

This example demonstrates how to load a Qwen 3 model and generate a response to a given prompt using the Hugging Face Transformers library.

Conclusion

Qwen 3 represents a significant milestone in Alibaba’s AI development, offering enhanced reasoning capabilities, scalability, and multimodal support. Its open-source availability under the Apache 2.0 license encourages widespread adoption and further innovation within the AI community. As the AI landscape continues to evolve, Qwen 3 positions Alibaba as a formidable player in both domestic and global arenas.

How to call Qwen 3 API from CometAPI

Qwen 3 API Pricing in CometAPI:

Required Steps

• Log in to cometapi.com. If you are not our user yet, please register first
• Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.
• Get the url of this site: https://api.cometapi.com/

Useage Methods

1. Select the “qwen3-235b-a22b“”qwen3-30b-a3b""qwen3-8b” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience.
2. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.
3. Insert your question or request into the content field—this is what the model will respond to.
4. . Process the API response to get the generated answer.

For Model lunched information in Comet API please see https://api.cometapi.com/new-model.

For Model Price information in Comet API please see https://api.cometapi.com/pricing.

See Also Qwen 2.5 Max API