Code Llama
Meta's open-source AI coding model
Code Llama is Meta's family of open-source large language models specialized for code generation, completion, and understanding. Built on Llama 2, it offers state-of-the-art performance among open models with support for infilling, large context windows up to 100K tokens, and zero-shot instruction following for programming tasks across multiple languages.
Key Capabilities
Code Llama generates code and natural language about code from both code and natural language prompts, supporting code completion, generation, and debugging. The model family includes three variants: foundation models (Code Llama), Python specializations (Code Llama - Python), and instruction-following models (Code Llama - Instruct), available in 7B, 13B, and 34B parameter sizes. All models are trained on 16K token sequences and show improvements on inputs up to 100K tokens. It supports Python, C++, Java, PHP, TypeScript, C#, Bash, and more.
Who Should Use Code Llama
Code Llama is ideal for developers and organizations who need an open-source, self-hostable code generation model without vendor lock-in. It is particularly valuable for researchers, companies with data privacy requirements that prevent using cloud-based AI services, and developers building custom AI-powered coding tools on top of an open foundation model.
Getting Started
Access Code Llama through Meta's AI research page or download the model weights from the official GitHub repository. Choose the variant that best fits your use case: the foundation model for general coding, the Python specialization for Python-heavy work, or the Instruct model for natural language interaction. Deploy locally or through cloud providers that host the model, such as AWS, Azure, or various inference APIs.
Pricing & Accessibility: Code Llama is completely free and open-source under the Llama 2 community license, available for both research and commercial use. No subscription or API fees apply when self-hosting. Cloud-hosted inference is available through various third-party providers at their respective rates.
Why Consider Code Llama: Code Llama provides state-of-the-art open-source code generation with full model weight access, enabling self-hosting, customization, and fine-tuning without vendor lock-in or ongoing subscription costs.
Pros
- Completely free and open-source for both research and commercial use
- Multiple model variants and sizes for different use cases and hardware
- 100K token context window supports large codebase analysis
- Self-hostable for full data privacy and no vendor lock-in
- State-of-the-art performance among open-source code models
Cons
- Requires significant hardware resources for local deployment of larger models
- No managed service or IDE integration out of the box
- Older model that has been superseded by newer Meta releases like Llama 3
Who is this for?
Self-hosted AI code generation for privacy-sensitive environments, custom coding tool development built on open models, Python-specialized code generation and completion, research and fine-tuning of code-focused language models, large codebase analysis with 100K token context
Frequently Asked Questions about Code Llama
Is Code Llama free for commercial use?
Yes, Code Llama is released under the Llama 2 community license which permits both research and commercial use. You can deploy it in production applications, build products on top of it, and fine-tune it for your specific needs without licensing fees.
What are the different Code Llama variants?
Code Llama comes in three variants: the foundation model for general code tasks, Code Llama - Python specialized for Python development, and Code Llama - Instruct optimized for natural language instruction following. Each is available in 7B, 13B, and 34B parameter sizes.
How does Code Llama compare to commercial coding assistants?
Code Llama achieves scores of up to 53% on HumanEval and 55% on MBPP benchmarks, placing it at the top of open-source models. While commercial tools may offer better IDE integration and higher benchmark scores, Code Llama provides full model access, self-hosting capability, and zero ongoing costs.
Pricing
free
Free
Free tier: Fully free and open-source with no usage limits
Details
APINo
Open SourceYes
LanguagesPython, C++, Java, PHP, TypeScript, C#, Bash
Learning CurveHard
Integrations
Self-hostedthird-party inference APIscustom integrations
