MODELS

Qwen3-Coder-Next

by Alibaba Qwen

modelalibaba-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 Jun 30, 2026