Qwen: Qwen3 Omni 30B A3B Instruct
qwen/qwen3-omni-30b-a3b-instruct
Access Qwen3 Omni 30B A3B Instruct from Qwen using the 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>
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 108
tokens / sec
Latency 0.87s
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 | 4.6% |
| LiveCodeBench Recent coding problems | 42.2% |
| 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 →
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Qwen3.6 Flash is the speed-optimized tier of Alibaba's Qwen3.6 model family, designed for high-throughput, low-latency inference pipelines. It sits alongside Qwen3.6 Max Preview, Plus, and 35B-A3B in the product lineup, targeting use cases where fast response times matter more than peak benchmark scores. Like other Qwen3.6 models, it builds on a hybrid architecture combining linear attention with sparse mixture-of-experts routing. It is best suited for high-volume production workloads such as classification, extraction, summarization, and lightweight agent tasks where latency and cost efficiency are the primary constraints.
ChatQwen3.5 Plus 2026-04-20
Qwen3.5 Plus is a proprietary hosted model from Alibaba, built on the Qwen3.5-397B-A17B Mixture-of-Experts architecture with 397 billion total parameters and 17 billion active per token. Its headline feature is a 1-million-token native context window — among the largest available via API — making it well suited for processing entire codebases, long documents, or extended multi-turn conversations in a single request. It supports both a deep-thinking mode and an "Auto" mode that adaptively invokes tools like web search and code interpreters. This April 20, 2026 snapshot reflects ongoing improvements to the model since its original February 2026 launch. The Qwen3.5 series demonstrated strong multimodal performance across reasoning, coding, and vision tasks. A solid general-purpose option for developers needing large-context capabilities without migrating to the newer Qwen3.6 line.
ChatQwen3.6 27B
Qwen3.6 27B is a dense 27-billion-parameter multimodal model from Alibaba's Qwen team, purpose-built for agentic coding and repository-level reasoning. It scores 77.2% on SWE-bench Verified and 59.3% on Terminal-Bench 2.0, outperforming the previous-generation Qwen3.5-397B-A17B across all major coding benchmarks despite being far smaller. It natively supports text, image, and video inputs with a 262K-token context window, extendable to 1M tokens. A standout feature is Thinking Preservation, which retains reasoning traces across conversation turns — reducing redundant computation in multi-step agent loops. The model uses a hybrid attention architecture combining Gated DeltaNet with traditional self-attention. Ideal for developers building coding agents, multi-turn tool-use workflows, or frontend generation pipelines.
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.
Qwen3 Omni 30B A3B Instruct is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| 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 6.0 on the Artificial Analysis Intelligence Index, outperforming 14% 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.
Add Qwen3 Omni 30B A3B Instruct to your app for free
Developers can integrate Qwen3 Omni 30B A3B Instruct for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.