MODELS
Qwen3-Coder-Next
by Alibaba Qwen
Overview
Open-weight Qwen coding-agent model for software engineering, tool calling, structured outputs, and long-context developer workflows.
Details
Qwen3-Coder-Next is an Alibaba Qwen coding-agent model. The official Qwen Hugging Face model card describes it as an open-weight model with 80B total parameters, 3B active parameters, Apache-2.0 licensing, a 262,144-token context length, tool-calling examples, and deployment guidance. The QwenLM GitHub repository says it is built on Qwen3-Next-80B-A3B-Base with hybrid attention and MoE, and is trained for executable coding tasks, environment interaction, and reinforcement learning. Alibaba Cloud Model Studio documentation shows qwen3-coder-next can be called through OpenAI-compatible Chat Completions with a Model Studio API key and DashScope-compatible endpoint.
When to Use
Use for coding-agent and software-engineering workflows where Qwen model compatibility is desired. Use when you need long-context coding assistance; the Qwen model card lists a 262 144-token context length. Use for tool-calling or function-calling style developer workflows supported by the model card and Alibaba Cloud documentation. Use when you want an Apache-2.0 open-weight coding model with deployment guidance from Qwen.
Getting Started
- Review the Qwen/Qwen3-Coder-Next Hugging Face model card for model details
- license
- tool-calling examples
- and deployment guidance.
- Check the QwenLM/Qwen3-Coder GitHub repository for project materials and implementation notes.
- For hosted API use
- follow Alibaba Cloud Model Studio’s qwen3-coder-next documentation and call it through OpenAI-compatible Chat Completions with a Model Studio API key and DashScope-compatible endpoint.
- Review Alibaba Cloud Model Studio pricing before production use.
Key Features
- •80B total parameters and 3B active parameters
- •according to the official Qwen Hugging Face model card.
- •262
- •144-token context length listed on the Qwen model card; AWS Bedrock lists a 256K context window.
- •Built on Qwen3-Next-80B-A3B-Base with hybrid attention and MoE
- •according to the QwenLM GitHub repository.
- •Trained for executable coding tasks
- •environment interaction
- •and reinforcement learning
- •according to the QwenLM GitHub repository.
- •Tool-calling examples and deployment guidance are provided on the Qwen Hugging Face model card.
- •Alibaba Cloud Model Studio supports OpenAI-compatible Chat Completions access for qwen3-coder-next.
Capabilities
- •code generation
- •software engineering assistance
- •tool calling
- •function calling
- •structured outputs
- •long-context processing
- •environment interaction
- •executable coding tasks
Last updated Jul 31, 2026