// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "qwen/qwen3.5-9b"
}).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/qwen3.5-9b"
}).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/qwen3.5-9b",
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/qwen3.5-9b",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
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.
Context Window 256K
tokens
Max Output 33K
tokens
Input Cost $0.05
per million tokens
Output Cost $0.15
per million tokens
Release Date Mar 10, 2026
Model Playground
Try Qwen3.5-9B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
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.
ChatQwen3.5-122B-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.
ChatQwen3.5-27B
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.
Frequently Asked Questions
You can access Qwen3.5-9B 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen3.5-9B to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.05 |
| Output | $0.15 |
Qwen3.5-9B was created by Qwen and released on Mar 10, 2026.
Qwen3.5-9B supports a context window of 256K tokens. For reference, that is roughly equivalent to 512 pages of text.
Qwen3.5-9B can generate up to 33K tokens in a single response.
Yes — the Qwen3.5-9B 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 Qwen3.5-9B to your app without worrying about API keys or setup.
Read the Docs View Tutorials