Qwen: Qwen3 Coder Next

Access Qwen3 Coder Next from Qwen using Puter.js AI API.

Get Started

Model Card

Qwen3-Coder-Next is an open-weight coding model from Alibaba's Qwen team with 80B total parameters but only 3B active per token, designed specifically for coding agents and local development with a 256K context window. It uses a sparse Mixture-of-Experts (MoE) architecture with hybrid attention, trained on 800K executable coding tasks using reinforcement learning to excel at long-horizon reasoning, tool calling, and recovering from execution failures. It achieves performance comparable to models with 10-20x more active parameters on benchmarks like SWE-Bench while maintaining low inference costs.

Context Window N/A

tokens

Max Output 66K

tokens

Input Cost $0.12

per million tokens

Output Cost $0.75

per million tokens

Release Date Feb 3, 2026

 

API Usage Example

Add Qwen3 Coder Next to your app with just a few lines of code.
No backend, no configuration required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "qwen/qwen3-coder-next"
}).then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "qwen/qwen3-coder-next"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="qwen/qwen3-coder-next",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)

curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "qwen/qwen3-coder-next",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

View full documentation →

More AI Models From Qwen

Chat

Qwen3.5-9B

Qwen 3.5 9B is a 9-billion parameter open-source multimodal model by Alibaba's Qwen Team, featuring a 262K native context window (extendable to ~1M tokens), support for text, image, and video input, and coverage of 201 languages. It uses a hybrid Gated DeltaNet architecture and outperforms much larger models like Qwen3-30B and OpenAI's gpt-oss-120B on key benchmarks including reasoning, vision, and document understanding.

 Chat

Qwen3.5-122B-A10B

Qwen 3.5 122B (10B Active) is Alibaba's largest medium-sized MoE model, activating only 10B of its 122B total parameters per inference pass. It excels at agentic tasks like tool use and multi-step reasoning, leading the Qwen 3.5 lineup on benchmarks such as BFCL-V4 and BrowseComp. It supports 262K native context (extendable to 1M), native multimodal input, and 201 languages under Apache 2.0.

 Chat

Qwen3.5-27B

Qwen 3.5 27B is the only dense (non-MoE) model in the Qwen 3.5 medium series, activating all 27B parameters on every forward pass for maximum per-token reasoning density. It ties GPT-5 mini on SWE-bench Verified at 72.4 and is competitive with Claude Sonnet 4.5 on visual reasoning benchmarks. It runs well on consumer hardware and is open-weight under Apache 2.0.

View all Qwen models →

Frequently Asked Questions

How do I use Qwen3 Coder Next?

You can access Qwen3 Coder Next by Qwen through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Qwen3 Coder Next free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen3 Coder Next to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Qwen3 Coder Next?
Pricing for Qwen3 Coder Next is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.12
Output$0.75
Who created Qwen3 Coder Next?

Qwen3 Coder Next was created by Qwen and released on Feb 3, 2026.

What is the max output length of Qwen3 Coder Next?

Qwen3 Coder Next can generate up to 66K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Qwen3 Coder Next API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add Qwen3 Coder Next to your app without worrying about API keys or setup.

Read the Docs View Tutorials