Qwen: Qwen3 4B

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Qwen3 4B is a compact model rivaling Qwen2.5-72B-Instruct performance, featuring hybrid thinking modes and 119 language support.

Context Window N/A

tokens

Max Output N/A

tokens

Input Cost $0

per million tokens

Output Cost $0

per million tokens

Release Date Apr 29, 2025

 

API Usage Example

Add AI 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").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").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="MODEL_ID",
    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": "MODEL_ID",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

View full documentation →

More AI Models From Qwen

Chat

Qwen3.6 Plus

Qwen 3.6 Plus is Alibaba's flagship large language model, built on a hybrid architecture combining linear attention with sparse mixture-of-experts routing for high throughput and scalability. It's optimized for agentic coding and complex multi-step workflows. On Terminal-Bench 2.0, it scores 61.6, surpassing Claude 4.5 Opus (59.3), while its 78.8 on SWE-bench Verified places it close behind. It also leads on MCPMark (48.2%) for tool-calling reliability. A native multimodal model, it handles text, images, and documents within a 1M-token context window with up to 65K output tokens. Notable features include always-on chain-of-thought reasoning, native function calling, and a preserve_thinking parameter that retains reasoning across multi-turn agent loops. A strong fit for developers building AI coding agents, terminal automation, and tool-using pipelines.

 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.

View all Qwen models →

Frequently Asked Questions

How do I use Qwen3 4B?

You can access Qwen3 4B 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 4B free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen3 4B 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 4B?
Pricing for Qwen3 4B is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0
Output$0
Who created Qwen3 4B?

Qwen3 4B was created by Qwen and released on Apr 29, 2025.

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

Yes — the Qwen3 4B 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.

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