Qwen: Qwen3.8 27B Abliterated Cyber
qwen/qwen3.8-27b-abliterated-cyber:free
Try Qwen3.8 27B Abliterated Cyber 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-abliterated-cyber:free"
}).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-abliterated-cyber:free"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Qwen3.8 27B Abliterated Cyber is a free, community fine-tune of Alibaba's Qwen3.8 27B, served through the Infron aggregator rather than directly by Alibaba or the Qwen team.
"Abliterated" refers to abliteration, a technique that identifies and removes the internal activation direction responsible for a model's safety refusals, rather than retraining it from scratch. Applied here, it produces a variant that answers prompts a standard instruction-tuned release would decline.
The "Cyber" in its name points to a cybersecurity focus, suggesting use in exploit and malware analysis, penetration-testing scripts, and other security research work that base Qwen models often refuse. We found no independent documentation of who built this specific variant or how it performs, so benchmark claims can't be verified.
It offers a 256,000-token context window and up to 131,072 output tokens at no cost, useful for testing uncensored, security-oriented prompts before committing to a paid model.
Context Window 256K
tokens
Max Output 131K
tokens
Input Cost $0
per million tokens
Output Cost $0
per million tokens
Release Date N/A
Try Qwen3.8 27B Abliterated Cyber for free
Try Qwen3.8 27B Abliterated Cyber instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
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.
ChatQwen3.6 Max Preview
Qwen3.6 Max Preview is Alibaba's most capable language model to date — a proprietary flagship that claimed the top score on six major coding benchmarks at its April 20, 2026 release. It leads on SWE-bench Pro, Terminal-Bench 2.0, SkillsBench, QwenClawBench, QwenWebBench, and SciCode. The Artificial Analysis Intelligence Index rates it at 52, well above the median for reasoning models in its price tier. It supports a 256K-token context window and is text-only at launch. As a preview release, Alibaba is still actively iterating on the model. Best suited for teams building coding agents, scientific computing tools, or frontend generation systems that need peak benchmark performance.
ChatQwen3.6 35B A3B
Qwen3.6 35B A3B is a sparse Mixture-of-Experts model with 35 billion total parameters but only 3 billion active per token, making it highly efficient for inference. Developed by Alibaba's Qwen team, it scores 73.4% on SWE-bench Verified and 51.5% on Terminal-Bench 2.0 — significantly outperforming dense models like Gemma 4-31B (52.0% on SWE-bench Verified). It natively handles text, image, and video with a 262K-token context window, extendable to 1M tokens. The model supports Thinking Preservation for stable multi-turn reasoning and includes native tool-calling capabilities. Released under Apache 2.0, it was the first open-weight model in the Qwen3.6 family. A strong choice for developers who want frontier-adjacent coding performance at a fraction of the compute cost of larger models.
Frequently Asked Questions
You can access Qwen3.8 27B Abliterated Cyber 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.
Qwen3.8 27B Abliterated Cyber 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.
Qwen3.8 27B Abliterated Cyber 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 |
| Output | $0 |
Qwen3.8 27B Abliterated Cyber supports a context window of 256K tokens. For reference, that is roughly equivalent to 512 pages of text.
Qwen3.8 27B Abliterated Cyber can generate up to 131K tokens in a single response.
Yes — the Qwen3.8 27B Abliterated Cyber 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 Abliterated Cyber to your app for free
Developers can integrate Qwen3.8 27B Abliterated Cyber for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.