Overview
CodeLlama is Meta's code-specialized model built on the Llama architecture. Trained on code-specific datasets, it excels at code generation, debugging, refactoring, and documentation across multiple programming languages.
Sizes
7B / 13B / 34B / 70B
Context Window
16K-100K tokens
Languages
Python, Java, C++, JS, more
License
Llama Community
✅Strengths
- ✓Code-specialized training for better accuracy
- ✓Multiple sizes for different hardware
- ✓Supports code infilling (complete partial code)
- ✓Open weights - run locally in VS Code, Cursor
- ✓Strong multilingual code support
⚠️Weaknesses
- ✗Less capable than general models for non-code tasks
- ✗Older training data than newer Llama versions
- ✗May generate outdated code patterns
- ✗Requires code-specific prompting
Best Use Cases
💻 Code Completion
IDE autocomplete
🐛 Debugging
Error diagnosis
🔄 Refactoring
Code improvement
📝 Documentation
Comments, docstrings
🧪 Test Generation
Unit tests, fixtures
🎓 Learning
Code explanations
Benchmarks
HumanEval (34B)48.8%
HumanEval (70B)57.3%
MBPP (34B)57.0%