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What is Qwen Code?

Qwen3-Coder is a sophisticated coding model available in multiple sizes, with its standout 480B-parameter Mixture-of-Experts variant (featuring 35B active parameters) capable of handling 256K-token contexts that can be expanded to 1M, showcasing superior performance in Agentic Coding, Browser-Use, and Tool-Use tasks, effectively competing with Claude Sonnet 4. The model undergoes a pre-training phase that utilizes a staggering 7.5 trillion tokens, of which 70% consist of code, alongside synthetic data improved from Qwen2.5-Coder, thereby boosting its coding proficiency and overall functionality. Its post-training phase benefits from extensive execution-driven reinforcement learning across 20,000 parallel environments, allowing it to tackle complex multi-turn software engineering tasks like SWE-Bench Verified without requiring test-time scaling. Furthermore, the open-source Qwen Code CLI, adapted from Gemini Code, enables the implementation of Qwen3-Coder in agentic workflows through customized prompts and function calling protocols, ensuring seamless integration with platforms like Node.js and OpenAI SDKs. This blend of powerful features and versatile accessibility makes Qwen3-Coder an invaluable asset for developers aiming to elevate their coding endeavors and streamline their workflows effectively. As a result, it serves as a pivotal resource in the rapidly evolving landscape of programming tools.

What is Patronus AI?

Patronus AI is a research lab focused on the data and simulations that frontier AI models learn from. Its main offering is a catalog of reinforcement learning environments covering software engineering, computer use, customer service, and finance, each built to reflect how real applications behave rather than idealized versions of them. Agents receive tasks inside these simulated applications and are scored with reward signals, giving AI labs a way to improve performance on long, multi-step workflows. The company is also developing Digital World Models, which predict the behavior of digital environments and allow training environments to be generated at scale instead of being built one at a time by hand. These environments and models support the post-training and evaluation of AI agents that operate in software.

Media

Media

Integrations Supported

Alibaba AI Coding Plan
Claude Fable 5.1
Claude Fable 5.5
Claude Mythos 5
Claude Opus 4.1
Claude Opus 4.5
Claude Opus 4.6
Claude Opus 4.7
Claude Opus 5.5
Claude Sonnet 4
Claude Sonnet 4.5
Claude Sonnet 5.5
Melaya
OpenAI
OpenSpec
Qwen 4
Qwen3.8-27B
Qwen3.8-Flash-Next
Qwen3.8-Max
Step 5 Preview

Integrations Supported

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Custom pricing based on project scope. Contact Patronus AI to discuss.

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Qwen

Date Founded

2023

Company Location

China

Company Website

github.com/QwenLM/qwen-code

Company Facts

Organization Name

Patronus AI

Date Founded

2023

Company Location

United States

Company Website

www.patronus.ai/

Categories and Features

Agentic AI

Not specified

AI Coding Agents

Not specified

Categories and Features

Artificial Intelligence

Machine Learning
Natural Language Processing

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