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.
alibabaQwen3February 3, 2026About Qwen3-Coder-Next
Learn about Qwen3-Coder-Next's capabilities, features, and how it can help you achieve better results.
Model Architecture
Qwen3-Coder-Next is a specialized open-weight model designed by Alibaba Cloud for software engineering agents. It utilizes a Mixture-of-Experts (MoE) architecture with 80 billion total parameters, but it only activates 3 billion parameters per token. This design combines the intelligence of a massive model with the inference speed of a small one. The architecture includes a hybrid attention mechanism, integrating Gated DeltaNet with standard Gated Attention to process contexts up to 262,144 tokens.
Agentic Specialization
The model is trained on over 800,000 verifiable coding tasks and executable environments. This training emphasizes long-horizon reasoning and the ability to recover from execution failures. It scores 70.8% on SWE-Bench Verified, demonstrating its capacity to handle multi-step development tasks from initial planning to final code execution. It excels in autonomous agentic frameworks like OpenClaw and Qwen Code.
Deployment and Privacy
Licensed under Apache 2.0, this model provides a secure alternative for developers who require local, private development environments. It can run on consumer-grade hardware with sufficient RAM through quantization. The high context window allows for repository-scale analysis without the performance degradation typically seen in smaller context models.
Use Cases
Discover the different ways you can use Qwen3-Coder-Next to achieve great results.
Autonomous Coding Agents
Powers frameworks to handle multi-step development tasks from planning to final execution.
Local Private Development
Runs elite coding assistance on consumer GPUs with 16GB VRAM using quantized MoE layers.
Large-Scale Repository Analysis
Processes entire codebases within its 256k window to identify technical debt.
Code Repair and Refactoring
Updates legacy code to modern standards by providing executable environment feedback.
Multilingual Scripting
Generates high-fidelity code across more than 40 programming languages including Rust and Go.
Interactive 3D Simulation
Builds complex web-based visualizers and simulations using rapid one-shot generation.
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-intl.aliyuncs.com/compatible-mode/v1",
});
async function main() {
const completion = await client.chat.completions.create({
model: "qwen3-coder-next",
messages: [
{ role: "system", content: "You are a professional coding assistant." },
{ role: "user", content: "Write a React component for a sortable list." },
],
});
console.log(completion.choices[0].message.content);
}
main();Install the SDK and start making API calls in minutes.
Community Feedback
See what the community thinks about Qwen3-Coder-Next
“Nearly matches Claude in overall coding capabilities. Beats Claude 3.5 Sonnet on HumanEval at 92.7%.”
“The efficiency of the MoE version is insane for local hardware. I am getting 26 TPS on a mid-range system.”
“Self-speculative decoding is mathematically impossible for Qwen Coder Next due to recurrent states.”
“Qwen3-Coder-Next is based on MoE, and way stronger and smarter than before!”
“Demonstrating the ability to switch providers mid-project with the new 480B model variants.”
“The agentic training recipe on 800k tasks shows in the way it recovers from build errors.”
Related Videos
Watch tutorials, reviews, and discussions about Qwen3-Coder-Next
“Allows it to be accessible for folks wanting to play with local AI coding agents”
“This to me is screaming open code test this model which I will do”
“The memory efficiency on this thing is a huge win”
“It handles complex logic better than the previous 72B dense model”
“This is the first open model that actually follows my terminal commands correctly”
“Qwen 3 coder Next also has only 3 billion active parameters to run on consumer graphics card”
“It works beautifully. I am really amazed I can get this result in one shot from local AI”
“80 billion parameters usually requires a cluster, but the MoE approach changes everything”
“It handles 40+ programming languages without any noticeable performance drop”
“Using it with OpenClaw makes it feel like having a junior dev on the team”
“Three billion parameter model going head-to-head with models 10 to 20 times of its size”
“Qwen 3 comes with a lot of advantages but with a lower cost”
“The 256k context is real, it did not hallucinate the middle of my project”
“The latency is surprisingly low given the 80B total parameter weight”
“It fixed a bug in my legacy Go repo that GPT-4o missed three times”
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Pro Tips
Expert tips to help you get the most out of Qwen3-Coder-Next and achieve better results.
Use Long System Prompts
Provide the model with detailed examples and documentation to align its agentic behavior.
Iterative Error Feedback
Feed browser console error logs back into the model for high-success rate self-correction.
Optimize Layer Offloading
Offload specific MoE expert layers to system RAM to balance inference speed and reasoning.
Align Sampling Parameters
Use a temperature of 1.0 with top_p 0.95 and top_k 40 for the most accurate coding results.
Testimonials
What Our Users Say
Join thousands of satisfied users who have transformed their workflow
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CEO, qannas.pro
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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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Frequently Asked Questions
Find answers to common questions about Qwen3-Coder-Next