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Qwen

Qwen: Qwen Flash

qwen/qwen-flash

Access Qwen Flash 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-flash"
}).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-flash"
        }).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-flash",
    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-flash",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Qwen Flash is Alibaba's latency-optimized general-purpose language model, designed as the successor to Qwen Turbo for cost-efficient, high-throughput workloads.

It offers a 1 million token context window with native support for context caching, making repeated or large-context requests significantly cheaper. The model supports function calling and is accessible via an OpenAI-compatible API through Alibaba Cloud Model Studio.

Qwen Flash is a strong choice for developers running high-volume production tasks — classification, extraction, summarization, and lightweight agentic pipelines — where low latency and predictable pricing matter more than peak reasoning capability. Its flexible tiered pricing and context cache support make it especially cost-effective at scale.

Context Window 1M

tokens

Max Output 33K

tokens

Input Cost $0.05

per million tokens

Output Cost $0.4

per million tokens

Input text

modalities

Tool Use Yes

 

Knowledge Cutoff Apr 2024

 

Release Date Jul 28, 2025

 

Model Playground

Try Qwen Flash instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat qwen/qwen-flash
Qwen
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Qwen3.8 2.4T A95B

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.

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Qwen3.8 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.

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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.

Frequently Asked Questions

How do I use Qwen Flash?

You can access Qwen Flash 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.

Is Qwen Flash free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Qwen Flash to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Qwen Flash?
Qwen Flash costs $0.05 per 1M input tokens and $0.4 per 1M output tokens.
Price per 1M tokens
Input$0.05
Output$0.4
Who created Qwen Flash?

Qwen Flash was created by Qwen and released on Jul 28, 2025.

What is the context window of Qwen Flash?

Qwen Flash supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,000 pages of text.

What is the max output length of Qwen Flash?

Qwen Flash can generate up to 33K tokens in a single response.

What is the knowledge cutoff of Qwen Flash?

Qwen Flash has a knowledge cutoff date of Apr 2024. This means the model was trained on data available up to that date.

What types of input can Qwen Flash process?

Qwen Flash accepts the following input types: text. It produces: text.

Does Qwen Flash support tool use (function calling)?

Yes, Qwen Flash supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Qwen Flash 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 Flash to your app without worrying about API keys or setup.

Read the Docs View Tutorials