Code Llama 70B is Meta's largest model in the Code Llama family, built on a Llama 2 foundation and further pre-trained on a large corpus of code and code-related text. At 70 billion parameters it is targeted at complex software engineering tasks — understanding large codebases, generating non-trivial algorithms, and producing detailed technical explanations. The Instruct variant also supports natural-language code instructions, making it suitable for chat-driven development workflows.
Meta designed Code Llama 70B to handle tasks that smaller code models handle poorly: multi-file reasoning, intricate refactoring, and answering deep architectural questions. It supports an extended fill-in-the-middle (FIM) capability for completion within existing code blocks, and it performs well on competitive programming benchmarks relative to models of comparable open-weights size.
Key Features
Designed for complex, multi-step software engineering tasks
Fill-in-the-middle (FIM) for in-context code completion
Strong performance on algorithmic and competitive programming problems
Supports natural-language-to-code instruction following
Broad language coverage including Python, Java, C++, JavaScript, and more
Open weights suitable for fine-tuning on domain-specific codebases
Ideal Use Cases
Automated code review and refactoring recommendations
Generating complex algorithms from natural-language specifications
IDE integration for intelligent multi-file code completion
Teaching and explaining advanced programming concepts
Building specialized coding assistants via domain fine-tuning
Example Prompts for Code Llama 70B
Technical Specifications
| Provider | Meta |
| Category | Code |
| Modality | Text -> Code |
Frequently Asked Questions
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