Qwen3-Coder-Next
Qwen3-Coder-Next is Alibaba Cloud's elite Apache 2.0 coding model, featuring an 80B MoE architecture and 256k context window for advanced local development.
alibabaQwen3-CoderFebruary 2, 2026About Qwen3-Coder-Next
Learn about Qwen3-Coder-Next's capabilities, features, and how it can help you achieve better results.
Model Overview
Qwen3-Coder-Next is a state-of-the-art open-weight language model designed by Alibaba Cloud's Qwen team, specifically optimized for coding agents and local development environments. Built upon the Qwen3-Next-80B-A3B-Base architecture, it utilizes a sophisticated Mixture-of-Experts (MoE) design with hybrid attention (Gated DeltaNet and Gated Attention). This allows the model to maintain a massive 80-billion-parameter knowledge base while activating only 3 billion parameters per token, resulting in flagship-level reasoning with the inference speed and memory footprint of a much smaller model.
Agentic Specialization
The model represents a shift toward scaling agentic training signals rather than just raw parameter count. It has been trained on over 800,000 verifiable coding tasks paired with executable environments, enabling it to learn directly from environment feedback. This specialized training recipe emphasizes long-horizon reasoning, tool usage, and the ability to recover from execution failures—capabilities that are critical for modern "vibe coding" workflows and autonomous agentic frameworks like OpenClaw.
Local Performance
With a native 256K context window that can extrapolate further, Qwen3-Coder-Next is uniquely positioned as the most powerful local-first coding assistant available. Released under the Apache 2.0 license, it empowers developers to build, debug, and ship entire codebases within a secure, private environment without relying on proprietary cloud APIs.
Use Cases for Qwen3-Coder-Next
Discover the different ways you can use Qwen3-Coder-Next to achieve great results.
Local Agentic Development
Powering autonomous coding agents that can plan, execute, and debug software locally without sensitive data leaving the machine.
Complex Web Prototyping
Generating functional full-stack applications, including 3D visualizations and interactive games, from single natural language prompts.
Large Repository Analysis
Utilizing the 256K context window to ingest and reason over entire multi-file project structures for refactoring and optimization.
Automated Security Auditing
Scanning codebases for complex vulnerabilities like SQL injection and plaintext credential exposure with grounded fix suggestions.
Technical Research Summarization
Scraping and parsing dense academic or technical documentation to produce organized, actionable HTML reports.
Cross-Language Systems Migration
Translating complex business logic and hardware-specific constraints between different programming languages with high fidelity.
Strengths
Limitations
API Quick Start
alibaba/qwen-3-coder-next
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: 'https://dashscope.aliyuncs.com/compatible-mode/v1'
});
async function main() {
const completion = await client.chat.completions.create({
model: 'qwen-3-coder-next',
messages: [{ role: 'user', content: 'Write a React hook for debouncing a value.' }],
});
console.log(completion.choices[0].message.content);
}
main();Install the SDK and start making API calls in minutes.
What People Are Saying About Qwen3-Coder-Next
See what the community thinks about Qwen3-Coder-Next
"This model is incredible for coding and stacks up favorably against the competition"
"The architecture allows for a massive context length without ballooning VRAM"
"Alibaba is crushing the open-weights game with this MoE architecture"
"Finally a local model that handles 256k context without feeling like a snail"
"I'm seeing a stable ~7.8 tok/s decode on CPU, which is plenty for a local code reviewer"
"Qwen3 Coder is basically the endgame for local development setups."
Videos About Qwen3-Coder-Next
Watch tutorials, reviews, and discussions about Qwen3-Coder-Next
“We have a 256k context length as well, which is very robust, especially for something that can be run locally.”
“We have our result at a speed of 26.17 tokens per second... quite a lengthy result.”
“This is a very exciting model... it shows extreme potential for agentic coding.”
“The accuracy on Python tasks is just staggering for an open weight model.”
“I think this model officially kills the need for paid coding assistants for most devs.”
“It's built on an active 3 billion parameter in a total 80 billion parameters model.”
“It's not just a coding AI model with 200k context window... it's absolutely intuitive.”
“For everyday users, you can simply ask it to scrape a web page, analyze content, and generate a clean report.”
“The way it handles multi-file projects locally is a game changer for privacy.”
“Function calling feels much more snappy compared to the previous version.”
“Writing stories at 62 tokens a second. Boom. That was fast.”
“We are bombing right now... 150 tokens a second with batching... this is amazing.”
“This car racing game was actually better than the version on Claude... got to give it that.”
“The MoE architecture really shines when you look at the token-per-watt efficiency.”
“Quantization doesn't seem to hurt the logic as much as I expected.”
Supercharge your workflow with AI Automation
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Pro Tips for Qwen3-Coder-Next
Expert tips to help you get the most out of Qwen3-Coder-Next and achieve better results.
Hardware Bandwidth Optimization
For the 80B scale, ensure your system utilizes high-channel memory to prevent inference bottlenecks on CPU-only setups.
Iterative Debugging
Feed the model's own runtime errors back into the prompt; it is specifically trained to recognize execution failures and refine its logic.
Context-Rich Prompting
Maximize the 256K window by providing relevant dependency files and architectural diagrams to reduce hallucinations.
Aesthetic Refinement
When generating UI, explicitly request color and CSS transitions to override the model's default tendency toward minimalist layouts.
Testimonials
What Our Users Say
Join thousands of satisfied users who have transformed their workflow
Jonathan Kogan
Co-Founder/CEO, rpatools.io
Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.
Mohammed Ibrahim
CEO, qannas.pro
I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!
Ben Bressington
CTO, AiChatSolutions
Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!
Sarah Chen
Head of Growth, ScaleUp Labs
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Founder, DataDriven.io
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Marketing Director, GrowthMetrics
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Jonathan Kogan
Co-Founder/CEO, rpatools.io
Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.
Mohammed Ibrahim
CEO, qannas.pro
I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!
Ben Bressington
CTO, AiChatSolutions
Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!
Sarah Chen
Head of Growth, ScaleUp Labs
We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.
David Park
Founder, DataDriven.io
The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!
Emily Rodriguez
Marketing Director, GrowthMetrics
Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.
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Frequently Asked Questions About Qwen3-Coder-Next
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