Qwen-Plus
VerifiedOpen-weight LLM excelling at million-token context tasks.
About Qwen-Plus
Qwen-Plus uses a transformer-based design tailored for extended sequences. Its fully open weights allow free modification, fine-tuning, and local deployment by the community. The architecture prioritizes efficient handling of very large text inputs.
A key strength is the one-million-token context window that accommodates entire documents or code repositories without truncation. Open-weight release fosters transparency, reproducibility, and collaborative improvements. Text-only modality keeps focus on core language modeling performance.
Users commonly apply it to long-document summarization, extended dialogue systems, and large-scale code analysis. Researchers integrate the model into custom pipelines for academic experiments and production tools. Its accessibility suits both individual projects and enterprise-scale text workflows.
Capabilities
How Qwen-Plus compares
Qwen-Plus (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen-Plus ranks #66 of 141
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-Document Analysis
Qwen-Plus processes and reasons over documents up to 1,000,000 tokens, making it effective for summarizing lengthy reports, legal contracts, or research papers while preserving critical details.
Multilingual Application Development
The model generates and translates text across languages, supporting global products that require consistent output in multiple languages within the same conversation or workflow.
Complex Technical Problem Solving
Qwen-Plus handles code generation, analysis, and mathematical reasoning tasks, enabling developers to debug large codebases or solve advanced algorithmic challenges.
Strengths & limitations
Strengths
- +Handles extremely long inputs effectively
- +Strong multilingual support including Chinese
- +Competitive reasoning and coding performance
- +Versatile instruction adherence
Limitations
- –Text-only modality with no vision support
- –Subject to regional content policies
- –Performance can vary on highly specialized domains
Cost calculator
Estimate what Qwen-Plus would cost for your usage.
Based on Qwen-Plus's $0.26/1M input · $0.78/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "qwen/qwen-plus",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen-plus
Editor's verdict
Qwen-Plus is Alibaba Qwen's open-weight language models with a 1000K-token context window.
At $0.78 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to handles extremely long inputs effectively and strong multilingual support including chinese.
Frequently asked questions
Qwen-Plus provides a context window of 1,000,000 tokens for processing extended inputs.
User reviews
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