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Qwen 2.5 Coder 32B InstructCode Like GPT-4o

Try Qwen 2.5 Coder 32B InstructAPI Documentation

Master Code Generation

SOTA Performance

Matches GPT-4o

Qwen 2.5 Coder 32B Instruct rivals GPT-4o on HumanEval, LiveCodeBench, and Aider benchmarks.

128K Context

Handles Long Code

Supports up to 128K tokens for complex projects and agentic workflows.

40+ Languages

Multi-Language Code

Excels in Haskell, Racket, and more via balanced pre-training data.

Examples

See what Qwen 2.5 Coder 32B Instruct can create

Copy any prompt below and try it yourself in the playground.

SQL Optimizer

“Analyze this SQL query for performance issues and rewrite it optimized for a PostgreSQL database handling large e-commerce datasets: SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id WHERE o.date > '2024-01-01' ORDER BY o.total DESC;”

Bug Fixer

“Fix bugs in this Python function that calculates Fibonacci numbers recursively, causing stack overflow for n>30: def fib(n): if n <= 1: return n return fib(n-1) + fib(n-2)”

API Generator

“Write a FastAPI endpoint for user authentication using JWT, including request validation with Pydantic and secure password hashing with bcrypt.”

Algorithm Impl

“Implement Dijkstra's shortest path algorithm in JavaScript for a graph represented as an adjacency list, with priority queue using heap.”

For Developers

A few lines of code.
Code fixes. One call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Qwen 2.5 Coder 32B Instruct

Read the docs

Qwen 2.5 Coder 32B Instruct is a 32B parameter LLM specialized for code generation, reasoning, and repair. It uses 64 Transformer layers with GQA and supports 128K context. Matches GPT-4o on key coding benchmarks.

Send prompts via the Qwen 2.5 Coder 32B Instruct API endpoint for instant code tasks. Integrates with agentic workflows and runs on standard inference setups. Scalable for production use.

Achieves 88.4% on HumanEval, 73.7% on Aider, and leads open models on LiveCodeBench. Outperforms GPT-4o on Spider and BIRD-SQL in some cases.

Yes, available on Hugging Face as open-weight model. Instruction-tuned for coding across 40+ languages. Fine-tune further for custom needs.

Alternatives include GPT-4o or Claude 3.5 Sonnet, but Qwen 2.5 Coder 32B Instruct offers better open-source value. Cost-effective for local runs with 32GB+ RAM.

Yes, excels at code repair on Aider benchmark at 73.7%. Handles debugging, error fixing, and refactoring efficiently.

Ready to create?

Start generating with Qwen 2.5 Coder 32B Instruct on ModelsLab.

Try Qwen 2.5 Coder 32B InstructAPI Documentation