Qwen: Qwen-MT Lite
qwen/qwen-mt-lite
Access Qwen-MT Lite from Qwen using the 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-mt-lite"
}).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-mt-lite"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Qwen-MT Lite is the lowest-cost tier of Alibaba's Qwen-MT machine translation family, built for simple, latency-sensitive translation such as real-time chat and live comment translation.
It supports 31 languages, fewer than the 92 covered by Qwen-MT Plus and Qwen-MT Turbo, and Alibaba's model comparison rates it as basic quality at the fastest speed and lowest cost of the tiers. Unlike the higher tiers, it does not support domain prompting. It does support incremental streaming output, where each response contains only newly generated content.
Best suited for developers translating short, high-volume text (chat messages, comments, UI strings) where response speed and price matter more than translation fidelity. For terminology control or higher output quality, Qwen-MT Plus or Turbo are the better fit.
Context Window 16K
tokens
Max Output 8K
tokens
Input Cost $0.12
per million tokens
Output Cost $0.36
per million tokens
Input text
modalities
Tool Use No
Release Date Jul 2025
Model Playground
Try Qwen-MT Lite instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Qwen
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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.
ChatQwen3.5 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.
ChatQwen3.6 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
You can access Qwen-MT Lite 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-MT Lite 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 | $0.12 |
| Output | $0.36 |
Qwen-MT Lite was created by Qwen and released on Jul 2025.
Qwen-MT Lite supports a context window of 16K tokens. For reference, that is roughly equivalent to 33 pages of text.
Qwen-MT Lite can generate up to 8K tokens in a single response.
Qwen-MT Lite accepts the following input types: text. It produces: text.
No, Qwen-MT Lite does not currently support tool use (function calling).
Yes — the Qwen-MT Lite 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-MT Lite to your app for free
Developers can integrate Qwen-MT Lite for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.