Qwen2.5 7B Instruct
VerifiedOpen-weight 7B instruct model with 128K context for versatile text tasks.
About Qwen2.5 7B Instruct
Qwen2.5 7B Instruct follows a transformer architecture released with fully accessible weights. Its open-weight release allows fine-tuning and local deployment by developers and researchers. The 131072-token context window enables handling of extended documents and multi-turn conversations.
Strengths include efficient operation at the 7B scale combined with strong instruction adherence. Typical usage covers chat interfaces, content summarization, and code-related tasks where users need reliable text generation without proprietary restrictions.
Capabilities
How Qwen2.5 7B Instruct compares
Qwen2.5 7B Instruct (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen2.5 7B Instruct ranks #8 of 141
Nova Micro 1.0Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long document analysis
The model excels at reasoning over extended inputs due to its 131072-token context window, enabling coherent processing of lengthy reports or conversations.
Code generation tasks
It performs well in writing, debugging, and optimizing code across languages while following precise developer instructions.
Multilingual problem solving
Users can leverage its multilingual capabilities for mathematical or logical tasks in non-English languages with strong instruction adherence.
Strengths & limitations
Strengths
- +Strong coding and math performance for its size
- +Efficient inference on consumer hardware
- +Handles very long contexts effectively
- +Solid multilingual capabilities
Limitations
- –Smaller parameter count limits depth on complex tasks
- –Text-only modality
- –May require careful prompting for best results
Cost calculator
Estimate what Qwen2.5 7B Instruct would cost for your usage.
Based on Qwen2.5 7B Instruct's $0.04/1M input · $0.10/1M 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-2.5-7b-instruct",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen-2.5-7b-instruct
Editor's verdict
Qwen2.5 7B Instruct is Alibaba Qwen's open-weight language models with a 131K-token context window.
At $0.10 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 strong coding and math performance for its size and efficient inference on consumer hardware.
Frequently asked questions
The model supports a context length of 131072 tokens.
User reviews
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