Qwen: Qwen-Omni Turbo
qwen/qwen-omni-turbo
Access Qwen-Omni Turbo 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/qwen-omni-turbo"
}).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/qwen-omni-turbo"
}).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/qwen-omni-turbo",
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/qwen-omni-turbo",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Qwen-Omni Turbo is Alibaba's cost-optimized omnimodal API model, built to process text, image, audio, and video inputs and return text responses in a single unified interface.
It is the lighter, faster tier in the Qwen-Omni family, designed for developers who need full multimodal coverage at lower latency and cost than the flagship Qwen-Omni model. Audio files up to 40 seconds and video files up to 150 MB are supported, spanning common formats such as MP3, WAV, MP4, and MOV. The model handles tool calling natively and is accessible via an OpenAI-compatible API.
Best suited for developers building applications that need to reason across mixed media inputs — such as audio transcription pipelines, video understanding workflows, or multimodal chatbots — where throughput and cost efficiency matter.
Context Window 33K
tokens
Max Output 2K
tokens
Input Cost $0.07
per million tokens
Output Cost $0.27
per million tokens
Input text, image, audio, video
modalities
Tool Use Yes
Knowledge Cutoff Apr 2024
Release Date Jan 19, 2025
Model Playground
Try Qwen-Omni Turbo instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
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Qwen3.8 2.4T A95B is Alibaba's open-weight release of its Qwen3.8 Max flagship, a sparse mixture-of-experts model with 2.4 trillion total parameters and 95 billion active per token, routed across 512 experts. It uses a hybrid attention design (Gated DeltaNet and Gated Attention layers) across 92 layers, with a native 262K context window and thinking mode enabled for every response. Alibaba reports 93.0 on PaperBench (ahead of GPT-5.6 Sol's 90.5), 92.6 on GPQA Diamond, 86.6 on Terminal-Bench 2.1, and 67.7 on SWE-bench Pro, positioning it for coding, research, and long-horizon agentic work. It gives developers access to Qwen-Max-class capability under open weights, useful for teams that want frontier-level coding and agentic performance without a closed API.
ChatQwen3.8 Max
Qwen3.8 Max is Alibaba's flagship large language model, released August 3, 2026 as the most capable model in the Qwen family to date. It uses a mixture-of-experts architecture with 2.4 trillion total parameters and about 95 billion active per request, and accepts text, image, and video input with a context window of up to 1 million tokens. Alibaba positions it for coding and long-horizon agentic work: in testing the model ran autonomously for over 10 days building a self-evolving software harness. Reported benchmarks include 93.0 on PaperBench, 82.8 on IFBench, 86.6 on Terminal-Bench 2.1, and 86.1 on OSWorld-Verified, ahead of Claude Opus 4.8 on several coding and agent tasks and roughly matching Claude Fable 5 and GPT-5.6 Sol, though it trails both on some evaluations. On the Arena.AI leaderboard it ranks as the top Chinese model for text tasks. Alibaba plans to open-source the weights on Hugging Face and ModelScope.
ChatQwen3.7 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.
Frequently Asked Questions
You can access Qwen-Omni Turbo 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 Qwen-Omni Turbo 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 | $0.07 |
| Output | $0.27 |
Qwen-Omni Turbo was created by Qwen and released on Jan 19, 2025.
Qwen-Omni Turbo supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Qwen-Omni Turbo can generate up to 2K tokens in a single response.
Qwen-Omni Turbo has a knowledge cutoff date of Apr 2024. This means the model was trained on data available up to that date.
Qwen-Omni Turbo accepts the following input types: text, image, audio, video. It produces: text.
Yes, Qwen-Omni Turbo supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Qwen-Omni Turbo 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 Qwen-Omni Turbo to your app without worrying about API keys or setup.
Read the Docs View Tutorials