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Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

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Description

Qwen3-Coder is an advanced code model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version (with 35B active) that inherently accommodates 256K-token contexts, which can be extended to 1M, and demonstrates cutting-edge performance in Agentic Coding, Browser-Use, and Tool-Use activities, rivaling Claude Sonnet 4. With a pre-training phase utilizing 7.5 trillion tokens (70% of which are code) and synthetic data refined through Qwen2.5-Coder, it enhances both coding skills and general capabilities, while its post-training phase leverages extensive execution-driven reinforcement learning across 20,000 parallel environments to excel in multi-turn software engineering challenges like SWE-Bench Verified without the need for test-time scaling. Additionally, the open-source Qwen Code CLI, derived from Gemini Code, allows for the deployment of Qwen3-Coder in agentic workflows through tailored prompts and function calling protocols, facilitating smooth integration with platforms such as Node.js and OpenAI SDKs. This combination of robust features and flexible accessibility positions Qwen3-Coder as an essential tool for developers seeking to optimize their coding tasks and workflows.

Description

Qwen3-Coder is a versatile coding model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version with 35B active parameters, which naturally accommodates 256K-token contexts that can be extended to 1M tokens. This model achieves impressive performance that rivals Claude Sonnet 4, having undergone pre-training on 7.5 trillion tokens, with 70% of that being code, and utilizing synthetic data refined through Qwen2.5-Coder to enhance both coding skills and overall capabilities. Furthermore, the model benefits from post-training techniques that leverage extensive, execution-guided reinforcement learning, which facilitates the generation of diverse test cases across 20,000 parallel environments, thereby excelling in multi-turn software engineering tasks such as SWE-Bench Verified without needing test-time scaling. In addition to the model itself, the open-source Qwen Code CLI, derived from Gemini Code, empowers users to deploy Qwen3-Coder in dynamic workflows with tailored prompts and function calling protocols, while also offering smooth integration with Node.js, OpenAI SDKs, and environment variables. This comprehensive ecosystem supports developers in optimizing their coding projects effectively and efficiently.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Node.js Yes 
OpenAI Yes 
Qwen2.5 Yes 
Alibaba Cloud No 
Claude Fable 5 Yes 
Claude Haiku 5.5 Yes 
Claude Mythos 5.2 Yes 
Claude Opus 4.1 Yes 
Claude Opus 5.5 Yes 
Claude Sonnet 4.5 Yes 
Melaya Yes 
OpenClaw No 
Oxlo.ai No 
PrintHaus Yes 
Qwen 4 Yes 
Qwen3.8-2.4T-A95B Yes 
Qwen3.8-27B Yes 
QwenCloud Yes 
SuperBased Yes 
Together AI No 

Integrations

Node.js Yes 
OpenAI Yes 
Qwen2.5 Yes 
Alibaba Cloud Yes 
Claude Fable 5 No 
Claude Haiku 5.5 No 
Claude Mythos 5.2 No 
Claude Opus 4.1 No 
Claude Opus 5.5 No 
Claude Sonnet 4.5 No 
Melaya No 
OpenClaw Yes 
Oxlo.ai Yes 
PrintHaus No 
Qwen 4 No 
Qwen3.8-2.4T-A95B No 
Qwen3.8-27B No 
QwenCloud No 
SuperBased No 
Together AI Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Qwen

Founded

2023

Country

China

Website

github.com/QwenLM/qwen-code

Vendor Details

Company Name

Qwen

Founded

2023

Country

China

Website

qwenlm.github.io/blog/qwen3-coder/

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Product Features

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