Qwen: Qwen-MT Flash
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Qwen-MT Flash is a machine translation model from Alibaba's Qwen team, built on the Qwen3 architecture and positioned as the balanced tier of the Qwen-MT line for quality, speed, and cost.
It translates between 92 languages, including Chinese, English, Japanese, Korean, French, Spanish, German, Arabic, Thai, Indonesian, and Vietnamese. Like the other Qwen-MT models, it supports terminology intervention (custom glossaries for brand names and technical terms), domain prompting, and translation memory for consistent output across large documents. Unlike Qwen-MT Plus and Turbo, it also supports incremental streaming, where each response contains only newly generated text.
Alibaba's documentation recommends it for general translation scenarios such as website content, product descriptions, and everyday communication, with Qwen-MT Plus reserved for professional domains where output quality matters most.
Context Window 16K
tokens
Max Output 8K
tokens
Input Cost $0.16
per million tokens
Output Cost $0.49
per million tokens
Input text
modalities
Tool Use No
Release Date Jul 2025
Code Example
Add AI to your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Qwen
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.
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
Qwen-MT Flash is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.16 |
| Output | $0.49 |
Qwen-MT Flash was created by Qwen and released on Jul 2025.
Qwen-MT Flash supports a context window of 16K tokens. For reference, that is roughly equivalent to 33 pages of text.
Qwen-MT Flash can generate up to 8K tokens in a single response.
Qwen-MT Flash accepts the following input types: text. It produces: text.
No, Qwen-MT Flash does not currently support tool use (function calling).
Yes — the Qwen-MT 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.
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