Qwen2.5 7B Instruct
Reason. Code. Instruct.
Master Core Capabilities
Math Excellence
Qwen2.5 7B Instruct MATH
Achieves 75.5 on MATH, 91.6 on GSM8K, surpassing Llama3.1-8B.
Code Mastery
Qwen2.5 7B Instruct Coding
Scores 84.8 on HumanEval with specialized coding and math training.
Multilingual Support
Qwen2.5 7B Instruct Languages
Handles 29+ languages, long contexts to 128K tokens via RoPE and GQA.
Examples
See what Qwen2.5 7B Instruct can create
Copy any prompt below and try it yourself in the playground.
Math Proof
“Prove the Pythagorean theorem step-by-step using geometric arguments, then verify with coordinates. Output in LaTeX format.”
Code Debugger
“Debug this Python function that sorts a list but fails on duplicates: def sort_list(lst): return sorted(set(lst)). Explain fixes and rewrite.”
JSON Generator
“Create a JSON schema for a task management API with endpoints for tasks, users, and projects. Include validation rules.”
Multilingual Summary
“Summarize this English article on quantum computing in Spanish, then translate key terms to Japanese. Keep under 200 words.”
For Developers
A few lines of code.
Instruct. Five lines.
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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with Qwen2.5 7B Instruct on ModelsLab.