Qwen2.5 Coder 32B Instruct
VerifiedOpen-weight LLM optimized for code generation and programming tasks.
About Qwen2.5 Coder 32B Instruct
The model uses the Qwen2.5 architecture with 32 billion parameters and a 128k token context length. This setup supports processing extended codebases and complex multi-file projects. Instruction tuning aligns it for following detailed developer prompts in code-related scenarios.
Developers apply it to code completion, debugging, refactoring, and generating scripts or algorithms. Its open weights enable local deployment, fine-tuning on proprietary datasets, and integration into custom tools. The text modality concentrates performance on programming languages, documentation, and technical problem-solving.
Capabilities
Benchmarks & performance
Independent evaluation scores and measured speed.
Source: Artificial Analysis
How Qwen2.5 Coder 32B Instruct compares
Qwen2.5 Coder 32B Instruct (striped bar) vs other language models on intelligence, speed and price.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Qwen2.5 Coder 32B Instruct ranks #54 of 67
Price
USD per 1M output tokens · Lower is better · Qwen2.5 Coder 32B Instruct ranks #88 of 141
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Debugging and Error Analysis in Large Repositories
The model excels at identifying issues and providing fixes within extensive codebases thanks to its long-context code understanding and dedicated debugging capabilities.
Code Generation from Technical Specifications
It performs well when translating detailed technical instructions into functional code across multiple programming languages.
Code Completion and Editing in Extended Contexts
The model supports precise code completion and editing tasks that require maintaining coherence over 128000 tokens of surrounding code.
Strengths & limitations
Strengths
- +Strong coding specialization
- +Effective handling of large code contexts
- +Developer-oriented instruction tuning
- +Balanced performance at 32B scale
Limitations
- –Text-only modality
- –Weaker on non-coding tasks
- –Risk of code hallucinations in complex scenarios
Cost calculator
Estimate what Qwen2.5 Coder 32B Instruct would cost for your usage.
Based on Qwen2.5 Coder 32B Instruct's $0.66/1M input · $1.00/1M 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-coder-32b-instruct",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen-2.5-coder-32b-instruct
Editor's verdict
Qwen2.5 Coder 32B Instruct is Alibaba Qwen's open-weight language models with a 128K-token context window.
On independent testing it scores 12.9 on the Artificial Analysis Intelligence Index.
At $1.00 per 1M output tokens, it is mid-priced 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 specialization and effective handling of large code contexts.
Frequently asked questions
The model has a context window of 128000 tokens.
User reviews
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