Qwen: Qwen 3.5 Flash
qwen/qwen3.5-flash
Try Qwen 3.5 Flash 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/qwen3.5-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/qwen3.5-flash"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Qwen 3.5 Flash is the fast, low-cost tier of the Qwen 3.5 family from Alibaba's Qwen team, served as the hosted API version of the Qwen3.5-35B-A3B model. It uses a hybrid architecture that pairs linear attention with sparse mixture-of-experts routing, which keeps compute close to linear across its 1M token context window.
The model supports tool and function calling and accepts image input alongside text, with output up to 64K tokens per request. At $0.10 per million input tokens and $0.40 per million output tokens, it is priced for high-volume work such as classification, extraction, and lightweight agent loops where cost and context length matter more than peak reasoning. Qwen has not published benchmark scores for the Flash tier specifically.
This rolling route tracks the latest snapshot; the dated 02-23 snapshot is listed separately.
Context Window 1M
tokens
Max Output 66K
tokens
Input Cost $0.1
per million tokens
Output Cost $0.4
per million tokens
Input text, image, video
modalities
Tool Use Yes
Knowledge Cutoff Apr 2025
Release Date Feb 23, 2026
Try Qwen 3.5 Flash for free
Try Qwen 3.5 Flash 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 Qwen 3.5 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.
Qwen 3.5 Flash 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.
Qwen 3.5 Flash 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 | $0.1 |
| Output | $0.4 |
Qwen 3.5 Flash was created by Qwen and released on Feb 23, 2026.
Qwen 3.5 Flash supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,000 pages of text.
Qwen 3.5 Flash can generate up to 66K tokens in a single response.
Qwen 3.5 Flash has a knowledge cutoff date of Apr 2025. This means the model was trained on data available up to that date.
Qwen 3.5 Flash accepts the following input types: text, image, video. It produces: text.
Yes, Qwen 3.5 Flash 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 3.5 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.
Add Qwen 3.5 Flash to your app for free
Developers can integrate Qwen 3.5 Flash for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.