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Qwen

Qwen: Qwen3.8 27B

Try Qwen3.8 27B for free in your browser, and add it to your app for free with Puter.js AI API.

Try it free Add to your app
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "qwen/qwen3.8-27b"
}).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/qwen3.8-27b"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

Model Card

Qwen3.8 27B is a dense, open-weight multimodal model from Alibaba's Qwen team, released August 14, 2026 as a smaller member of the Qwen3.8 family alongside the flagship Qwen3.8 Max.

It combines Gated DeltaNet linear attention with standard gated attention across 64 layers, giving a 27 billion parameter dense model a native 262K token context window, extendable to 1M tokens. It accepts text, image, and video input, including hour-scale video and STEM diagrams.

Alibaba reports 61.7 on SWE-bench Pro and 73.0 on Terminal Bench 2.1, both improvements over the earlier Qwen3.6 27B, and 89.2 on GPQA Diamond.

Released under Apache 2.0, it gives developers an open-weight alternative to Qwen3.8 Max for coding and agentic tasks, at a fraction of the parameter count.

Context Window 1M

tokens

Max Output 131K

tokens

Input Cost $0.5

per million tokens

Output Cost $3

per million tokens

Input text, image, video

modalities

Tool Use Yes

 

Release Date Aug 14, 2026

 

Output Speed 42

tokens / sec

Latency 1.23s

time to first token

Try Qwen3.8 27B for free

Try Qwen3.8 27B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat qwen/qwen3.8-27b
Qwen
Chat with Qwen3.8 27B
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Benchmarks

How Qwen3.8 27B performs on standard evaluations.

Artificial Analysis
Intelligence Index
33.7
Better than 85% of tracked models
Artificial Analysis
Coding Index
68.1
Better than 77% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
90.5%
Humanity's Last Exam Cross-domain reasoning
33.9%
SciCode Scientific programming
46.6%
LCR Long-context reasoning
82.0%

Scores sourced from Artificial Analysis.

Find other Qwen models →

Chat

Qwen3.6 Flash

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.

Chat

Qwen3.5 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.

Chat

Qwen3.6 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

How do I use Qwen3.8 27B?

You can access Qwen3.8 27B 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.

Can I try Qwen3.8 27B for free?

Qwen3.8 27B is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.

Is the Qwen3.8 27B API free for developers?

Qwen3.8 27B 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.

What is the pricing for Qwen3.8 27B?
Qwen3.8 27B costs $0.5 per 1M input tokens and $3 per 1M output tokens.
Price per 1M tokens
Input$0.5
Output$3
Who created Qwen3.8 27B?

Qwen3.8 27B was created by Qwen and released on Aug 14, 2026.

What is the context window of Qwen3.8 27B?

Qwen3.8 27B 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 Qwen3.8 27B?

Qwen3.8 27B can generate up to 131K tokens in a single response.

What types of input can Qwen3.8 27B process?

Qwen3.8 27B accepts the following input types: text, image, video. It produces: text.

Does Qwen3.8 27B support tool use (function calling)?

Yes, Qwen3.8 27B supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

How does Qwen3.8 27B perform on benchmarks?

Qwen3.8 27B scores 33.7 on the Artificial Analysis Intelligence Index, outperforming 85% of tracked models. On coding, it scores 68.1 (outperforms 77% of models).

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

Yes — the Qwen3.8 27B 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 Qwen3.8 27B to your app for free

Developers can integrate Qwen3.8 27B for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.

Get started How pricing works