Codestral 22B

Overview

Codestral is a 22.2-billion-parameter code generation model released by Mistral AI on May 29, 2024. It is specifically designed for coding tasks and trained on over 80 programming languages. The model supports both code completion (fill-in-the-middle) and instruction-following for code-related tasks.

Key Specifications

• Parameters: 22.2 billion
• Context Window: 32,000 tokens
• Programming Languages: 80+
• Precision: BF16 tensor precision
• License: Mistral AI Non-Production License (MNPL-0.1)
• Release Date: May 29, 2024
• Architecture Type: Decoder-only Transformer

Programming Language Support

Codestral supports 80+ programming languages, including:

Popular Languages

• Python
• Java
• C/C++
• JavaScript/TypeScript
• Bash/Shell

Specialized Languages

• Swift
• Fortran
• Rust
• Go
• Ruby
• PHP
• SQL
• And 70+ more

Capabilities

Core Features

1. Code Completion (Fill-in-the-Middle)
   • Predicts code between a prefix and suffix
   • Context-aware completions
   • Supports all 80+ languages
2. Code Generation (Instruct Mode)
   • Writes complete functions from descriptions
   • Generates boilerplate code
   • Creates code based on natural language instructions
3. Test Generation
   • Automatically writes unit tests
   • Generates test cases for functions
   • Creates integration tests
4. Code Understanding
   • Answers questions about code snippets
   • Explains code functionality
   • Provides documentation suggestions

Technical Advantages

• 32K Context Window: Significantly larger than competitors (4K-16K)
• Multi-Language Proficiency: Trained on diverse programming ecosystems
• Efficient Architecture: 22B parameters optimized for code tasks
• Dual Operation Modes: Both FIM and Instruct available

IDE Integration

Supported Platforms

Direct Integrations:

• VSCode: Via Continue.dev and Tabnine
• JetBrains IDEs: Via Continue.dev and Tabnine
• LlamaIndex: Full integration
• LangChain: Full integration

Dedicated Endpoint

• API: codestral.mistral.ai
• Optimized for IDE use cases
• Supports both Instruct and Fill-In-the-Middle routes

Licensing

MNPL (Mistral AI Non-Production License)

Permitted Uses:

• Research purposes
• Testing and evaluation
• Non-commercial projects
• Educational use

Restricted Uses:

• Commercial applications require separate license
• Production environments need commercial license
• Revenue-generating projects require commercial agreement

Commercial Licensing:

• Available on demand from Mistral AI
• Contact team for production use cases

Use Cases

Development Workflows

• Real-time code completion in IDEs
• Automated test generation
• Code documentation
• Refactoring assistance
• Bug detection and fixing

Enterprise Applications

• Internal development tools
• Code review automation
• Legacy code understanding
• API integration code generation

Education & Research

• Teaching programming concepts
• Research on code generation
• Training material development
• Code pattern analysis

Deployment

API Access

• Dedicated endpoint: codestral.mistral.ai
• Available via Mistral AI platform
• Integration with development tools

Local Deployment

• Available on Ollama: codestral:22b
• Hugging Face model: mistralai/Codestral-22B-v0.1
• BF16 precision for efficient inference

Performance

Context Comparison

Model	Context Window
Codestral 22B	32K tokens
Typical Competitors	4K-16K tokens

The extended context window allows:

• Analysis of larger codebases
• Better understanding of multi-file contexts
• More accurate suggestions with broader context

Significance

Codestral represents:

• First major code-specialized model from Mistral AI
• Competitive alternative to GitHub Copilot and other coding assistants
• Open-weight approach to code generation (with licensing restrictions)
• Focus on developer productivity and IDE integration
• Balance between model size (22B) and practical deployment

The model demonstrates that specialized code models can be highly effective without requiring hundreds of billions of parameters.

Related Models

• Mistral 7B: General-purpose predecessor
• Mixtral 8x7B: MoE variant with code capabilities
• Mistral Large 2: Flagship model with strong code performance

Resources

• Official Announcement: https://mistral.ai/news/codestral
• Hugging Face: https://huggingface.co/mistralai/Codestral-22B-v0.1
• Ollama: https://ollama.com/library/codestral:22b
• Developer: Mistral AI

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Status: OK
Last Updated: 2025-12-25
Review: Completed and approved for publication