Qwen: Tongyi DeepResearch 30B A3B
qwen/tongyi-deepresearch-30b-a3b
Access Tongyi DeepResearch 30B A3B from Qwen using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "qwen/tongyi-deepresearch-30b-a3b"
}).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/tongyi-deepresearch-30b-a3b"
}).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/tongyi-deepresearch-30b-a3b",
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/tongyi-deepresearch-30b-a3b",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Tongyi DeepResearch 30B A3B is an agentic deep-research model from Alibaba's Tongyi lab, built on Qwen3-30B-A3B with a mixture-of-experts design that activates 3.3B of its 30.5B parameters per token. It is trained for long-horizon web research, multi-step information seeking, and report synthesis rather than general chat.
It scores 32.9 on Humanity's Last Exam, 43.4 on BrowseComp, 46.7 on BrowseComp-ZH, 75.0 on xbench-DeepSearch, and 90.6 on FRAMES, and the Tongyi team reports performance on par with OpenAI's Deep Research across these benchmarks. Training combines agentic continual pre-training, supervised fine-tuning, and reinforcement learning on fully synthetic data.
It runs in two inference modes, a native ReAct loop that needs no prompt engineering and a Heavy mode based on the IterResearch paradigm, which rebuilds a streamlined workspace each research round and can run agents in parallel. A fit for developers building autonomous research agents and deep search pipelines.
Context Window 131K
tokens
Max Output 131K
tokens
Input Cost $0.09
per million tokens
Output Cost $0.45
per million tokens
Release Date Sep 16, 2025
Model Playground
Try Tongyi DeepResearch 30B A3B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
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Frequently Asked Questions
You can access Tongyi DeepResearch 30B A3B 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 Tongyi DeepResearch 30B A3B 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 | $0.09 |
| Output | $0.45 |
Tongyi DeepResearch 30B A3B was created by Qwen and released on Sep 16, 2025.
Tongyi DeepResearch 30B A3B supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Tongyi DeepResearch 30B A3B can generate up to 131K tokens in a single response.
Yes — the Tongyi DeepResearch 30B A3B 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 Tongyi DeepResearch 30B A3B to your app without worrying about API keys or setup.
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