Qwen: Qwen3 Omni 30B A3B Instruct
qwen/qwen3-omni-30b-a3b-instruct
Access Qwen3 Omni 30B A3B Instruct 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/qwen3-omni-30b-a3b-instruct"
}).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-omni-30b-a3b-instruct"
}).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-omni-30b-a3b-instruct",
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-omni-30b-a3b-instruct",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Qwen3 Omni 30B A3B Instruct is a natively multimodal Mixture-of-Experts model from Alibaba's Qwen team, with 30 billion total parameters and about 3 billion active per token. It accepts text, image, audio, and video input, and uses a Thinker-Talker design that can stream speech as well as text, with a reported end-to-end first-packet latency of 234 ms.
The Qwen team reports state-of-the-art results on 22 of 36 audio and audio-visual benchmarks, and open-source state-of-the-art on 32, with speech recognition and voice conversation performance comparable to Gemini 2.5 Pro and ahead of GPT-4o-Transcribe. It covers 119 text languages, 19 speech input languages, and 10 speech output languages.
This Instruct variant answers directly without chain-of-thought (a separate Thinking variant does extended reasoning). It supports function calling and fits voice assistants, transcription, audio analysis, and multimodal chat.
Context Window 66K
tokens
Max Output 16K
tokens
Input Cost $0.25
per million tokens
Output Cost $0.97
per million tokens
Input text, image, audio, video
modalities
Tool Use Yes
Release Date Sep 22, 2025
Output Speed 106
tokens / sec
Latency 0.89s
time to first token
Model Playground
Try Qwen3 Omni 30B A3B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Qwen3 Omni 30B A3B Instruct performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 62.0% |
| Humanity's Last Exam Cross-domain reasoning | 5.1% |
| LiveCodeBench Recent coding problems | 42.2% |
| SciCode Scientific programming | 18.6% |
| AIME 2025 Advanced math exam | 52.3% |
| IFBench Instruction following | 31.2% |
| LCR Long-context reasoning | 0.0% |
| Terminal-Bench Hard Agentic terminal tasks | 1.5% |
| τ²-Bench Tool use / agents | 16.4% |
Scores sourced from Artificial Analysis.
Find other Qwen models →
Qwen3.7 Flash
Qwen3.7 Flash is the low-cost, fast tier of Alibaba's Qwen3.7 family, released in July 2026. It is a vision-language model that accepts text, image, and video input across a 1 million-token context window, with reasoning enabled by default and a 262K-token thinking budget. Alibaba positions it as an upgrade over Qwen3.6 Flash in multimodal understanding and agent execution, with better object recognition and spatial intelligence. It supports function calling and structured outputs. Pricing is tiered by prompt length. Requests under 32K input tokens cost $0.03/$0.13 per million, rising to $0.20/$0.80 above 256K. Alibaba published no benchmarks at launch. An independent vision evaluation by Roboflow measured strong object identification (84.4%) but weak OCR and object detection, so it fits high-volume multimodal tasks (classification, visual agents, lightweight extraction) better than document-heavy pipelines.
ChatQwen3.7 Plus
Qwen3.7 Plus is Alibaba's multimodal agent model, released in June 2026, combining vision-language understanding with full agentic capabilities across a 1 million-token context window. Unlike the text-only Qwen3.7 Max, Plus ingests images and video alongside text, processed through early-fusion training so vision and language are jointly understood from the first layer. This enables GUI grounding — the model can interpret screenshots and issue precise on-screen actions — scoring 79.0 on ScreenSpot Pro, placing it alongside Claude Computer Use and OpenAI Operator in the GUI automation tier. Beyond vision, it adds deep reasoning, self-programming, tool invocation, and autonomous iteration: the model writes and tests code, calls external APIs, and loops until the task is done. On the Artificial Analysis Intelligence Index it scores 53. Choose it over Qwen3.7 Max when your workflow requires image or video inputs, browser/desktop automation, or end-to-end agentic pipelines that combine seeing, reasoning, and doing.
ChatQwen3.7 Max
Qwen3.7 Max is Alibaba's flagship proprietary reasoning model, released in May 2026, built for long-horizon agentic workloads with a 1 million-token context window and a chain-of-thought reasoning architecture. It is purpose-built for complex, multi-step autonomous tasks. Alibaba demonstrated the model running for 35 hours without degradation, executing over 1,000 tool calls in a single session — making it a strong candidate for coding agents, automated pipelines, and deep document analysis. On benchmarks, it ranks 13th globally on LM Arena's text leaderboard and scores 56.6 on the Artificial Analysis Intelligence Index, making it the highest-ranked Chinese model on that index. It posted 90.2 on Arena-Hard v2 and 72.5 on SWE-Bench Verified. Qwen3.7 Max supports the Anthropic API protocol natively, so it integrates cleanly with tooling like Claude Code. It is well-suited for developers building coding assistants, research agents, or any API use case requiring extended reasoning over large contexts.
Frequently Asked Questions
You can access Qwen3 Omni 30B A3B Instruct 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 Omni 30B A3B Instruct 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 | $0.25 |
| Output | $0.97 |
Qwen3 Omni 30B A3B Instruct was created by Qwen and released on Sep 22, 2025.
Qwen3 Omni 30B A3B Instruct supports a context window of 66K tokens. For reference, that is roughly equivalent to 131 pages of text.
Qwen3 Omni 30B A3B Instruct can generate up to 16K tokens in a single response.
Qwen3 Omni 30B A3B Instruct accepts the following input types: text, image, audio, video. It produces: text.
Yes, Qwen3 Omni 30B A3B Instruct supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Qwen3 Omni 30B A3B Instruct scores 5.1 on the Artificial Analysis Intelligence Index, outperforming 15% of tracked models. On math, it scores 52.3 (outperforms 49% of models).
Yes — the Qwen3 Omni 30B A3B Instruct 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 Omni 30B A3B Instruct to your app without worrying about API keys or setup.
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