Qwen: Qwen3.5 27B Anko
qwen/qwen3.5-27b-anko
Access Qwen3.5 27B Anko 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/qwen3.5-27b-anko"
}).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/qwen3.5-27b-anko"
}).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/qwen3.5-27b-anko",
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/qwen3.5-27b-anko",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Qwen3.5 27B Anko is a community fine-tune of Qwen3.5 27B, built by Allura (allura-org) on top of ArliAI's derestricted version of the base model, which removes built-in refusal behavior via a weight-abliteration technique. Anko adds a LoRA trained on reasoning traces and responses, using data generated by Doubao Seed 2.0 Pro and Mini, aimed at improving coherence and cutting down on repetitive output.
It's distributed through the Infron aggregator and positioned for creative writing, roleplay, and general chat. The model card recommends a Claude-style system prompt and non-default sampling (temperature around 1.25 with min_p) rather than Qwen's stock settings.
Context is 262K tokens. No independent benchmark scores have been published for this variant.
Context Window 262K
tokens
Max Output 262K
tokens
Input Cost $0.31
per million tokens
Output Cost $0.31
per million tokens
Release Date N/A
Model Playground
Try Qwen3.5 27B Anko instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
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.
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.
ChatQwen3.7 Plus
Qwen3.7 Plus is Alibaba's multimodal agent model, released in June 2026, combining vision-language understanding with full agentic capabilities across a 1 million-token context window. Unlike the text-only Qwen3.7 Max, Plus ingests images and video alongside text, processed through early-fusion training so vision and language are jointly understood from the first layer. This enables GUI grounding — the model can interpret screenshots and issue precise on-screen actions — scoring 79.0 on ScreenSpot Pro, placing it alongside Claude Computer Use and OpenAI Operator in the GUI automation tier. Beyond vision, it adds deep reasoning, self-programming, tool invocation, and autonomous iteration: the model writes and tests code, calls external APIs, and loops until the task is done. On the Artificial Analysis Intelligence Index it scores 53. Choose it over Qwen3.7 Max when your workflow requires image or video inputs, browser/desktop automation, or end-to-end agentic pipelines that combine seeing, reasoning, and doing.
Frequently Asked Questions
You can access Qwen3.5 27B Anko 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 Qwen3.5 27B Anko 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 | $0.31 |
| Output | $0.31 |
Qwen3.5 27B Anko supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
Qwen3.5 27B Anko can generate up to 262K tokens in a single response.
Yes — the Qwen3.5 27B Anko 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 Qwen3.5 27B Anko to your app without worrying about API keys or setup.
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