What are the LLM models that excel on coding tasks?

Leon Chase

• 5 min read

Several Large Language Models (LLMs) have been specifically designed or fine-tuned to excel in coding tasks. These models are trained on vast amounts of code from various programming languages, enabling them to generate code, debug, refactor, and even explain complex algorithms. Below is a list of some of the best LLMs for coding tasks, along with their key features and strengths.

1. Codex (by OpenAI)

Overview:

  • Developer: OpenAI
  • Model Page: Codex
  • Description: Codex is a descendant of GPT-3, fine-tuned specifically for coding tasks. It powers GitHub Copilot, one of the most popular AI-powered coding assistants.

Key Features:

  • Multilingual Support: Supports multiple programming languages, including Python, JavaScript, Java, C++, and more.
  • Code Generation: Can generate entire functions or scripts based on natural language prompts.
  • Debugging: Helps identify and fix bugs in code.
  • Documentation: Can generate documentation or comments for existing code.
  • Integration: Powers GitHub Copilot, which integrates directly into IDEs like Visual Studio Code.

Best For:

  • Developers looking for an AI assistant that can generate high-quality code across multiple languages.
  • Real-time coding assistance in IDEs.

2. GitHub Copilot (Powered by Codex)

Overview:

  • Developer: GitHub (in collaboration with OpenAI)
  • Model Page: GitHub Copilot
  • Description: GitHub Copilot is an AI-powered coding assistant that uses Codex to provide real-time code suggestions, autocompletion, and generation within your IDE.

Key Features:

  • Real-Time Suggestions: Provides inline code suggestions as you type.
  • Multilingual: Supports a wide range of programming languages.
  • Context-Aware: Understands the context of your code and provides relevant suggestions.
  • IDE Integration: Works seamlessly with Visual Studio Code, JetBrains IDEs, and other popular editors.

Best For:

  • Developers who want real-time coding assistance directly within their IDE.
  • Teams looking to improve productivity through AI-driven code suggestions.

3. AlphaCode (by DeepMind)

Overview:

  • Developer: DeepMind
  • Model Page: AlphaCode
  • Description: AlphaCode is a model developed by DeepMind that focuses on solving competitive programming problems. It has demonstrated the ability to solve complex algorithmic challenges at a level comparable to human competitors.

Key Features:

  • Algorithmic Problem Solving: Excels at solving competitive programming problems, including those found in coding competitions like Codeforces.
  • Reasoning: Demonstrates strong reasoning capabilities when tackling complex algorithmic tasks.
  • Language Support: Primarily focused on Python and C++ but can handle other languages as well.

Best For:

  • Competitive programmers and developers working on algorithmic challenges.
  • Solving complex, multi-step coding problems.

4. CodeWhisperer (by Amazon)

Overview:

  • Developer: Amazon Web Services (AWS)
  • Model Page: CodeWhisperer
  • Description: CodeWhisperer is Amazon's AI-powered coding assistant that helps developers write code faster by providing real-time code suggestions, detecting security vulnerabilities, and offering best practices.

Key Features:

  • Real-Time Suggestions: Provides inline code suggestions similar to GitHub Copilot.
  • Security Scanning: Detects potential security vulnerabilities in your code.
  • Multilingual Support: Supports Python, Java, JavaScript, TypeScript, and more.
  • Cloud Integration: Seamlessly integrates with AWS services and cloud infrastructure.

Best For:

  • Developers working within the AWS ecosystem.
  • Teams looking for both coding assistance and security scanning.

5. StarCoder (by BigCode)

Overview:

  • Developer: BigCode (a collaboration between Hugging Face and ServiceNow)
  • Model Page: StarCoder
  • Description: StarCoder is an open-source LLM trained on a large dataset of code from GitHub. It supports over 80 programming languages and is designed for code generation, completion, and understanding.

Key Features:

  • Open Source: Fully open-source and freely available for use.
  • Multilingual Support: Supports over 80 programming languages, including Python, Java, C++, JavaScript, and more.
  • Code Completion: Provides accurate code completions and suggestions.
  • Customizability: Can be fine-tuned for specific use cases or domains.

Best For:

  • Developers looking for an open-source alternative to proprietary models like Codex.
  • Teams that need flexibility and control over their coding assistant.

6. WizardCoder (by WizardLM)

Overview:

  • Developer: WizardLM
  • Model Page: WizardCoder
  • Description: WizardCoder is a fine-tuned version of the LLaMA model, specifically optimized for coding tasks. It performs exceptionally well in generating code and solving programming problems.

Key Features:

  • Fine-Tuned for Coding: Trained on a large corpus of code and programming-related data.
  • High Accuracy: Performs well on benchmarks like HumanEval and MBPP (standard benchmarks for evaluating code generation models).
  • Open Source: Fully open-source and freely available for use.

Best For:

  • Developers looking for a high-performing, open-source model for coding tasks.
  • Teams that want to fine-tune the model for specific coding needs.

7. CodeGen (by Salesforce)

Overview:

  • Developer: Salesforce Research
  • Model Page: CodeGen
  • Description: CodeGen is a family of open-source models designed for code generation. It includes several variants, such as CodeGen-Mono (monolingual) and CodeGen-Multi (multilingual).

Key Features:

  • Open Source: Fully open-source and freely available for use.
  • Multilingual Support: Supports multiple programming languages, including Python, JavaScript, and Go.
  • Code Generation: Capable of generating entire functions or scripts from natural language descriptions.
  • Customizability: Can be fine-tuned for specific use cases or domains.

Best For:

  • Developers looking for an open-source model that can generate code across multiple languages.
  • Teams that need flexibility and control over their coding assistant.

8. PaLM-Coder (by Google)

Overview:

  • Developer: Google
  • Model Page: PaLM-Coder
  • Description: PaLM-Coder is a variant of Google's PaLM model, fine-tuned specifically for coding tasks. It demonstrates strong performance in generating code and solving programming problems.

Key Features:

  • High-Quality Code Generation: Generates accurate and efficient code across multiple languages.
  • Reasoning: Demonstrates strong reasoning capabilities when tackling complex coding tasks.
  • Proprietary: Not fully open-source; access may be limited to researchers or enterprise users.

Best For:

  • Developers looking for a high-performing, proprietary model for coding tasks.
  • Teams that need advanced reasoning capabilities for complex coding problems.

9. BLOOM (by BigScience)

Overview:

  • Developer: BigScience
  • Model Page: BLOOM
  • Description: BLOOM is a large multilingual language model that can also handle coding tasks. While it is not specifically fine-tuned for coding, it has shown decent performance in generating code due to its broad training data.

Key Features:

  • Multilingual Support: Supports over 46 natural languages and 13 programming languages.
  • General-Purpose: Can handle both text-based and coding tasks.
  • Open Source: Fully open-source and freely available for use.

Best For:

  • Developers looking for a general-purpose model that can handle both text and code.
  • Teams that need a single model for multiple tasks, including coding.

10. PolyCoder (by Carnegie Mellon University)

Overview:

  • Developer: Carnegie Mellon University
  • Model Page: PolyCoder
  • Description: PolyCoder is an open-source LLM trained specifically on code. It supports multiple programming languages and is designed for code generation and completion tasks.

Key Features:

  • Open Source: Fully open-source and freely available for use.
  • Multilingual Support: Supports multiple programming languages, including Python, Java, and C++.
  • Code Generation: Capable of generating entire functions or scripts from natural language descriptions.

Best For:

  • Developers looking for an open-source model that can generate code across multiple languages.
  • Teams that need flexibility and control over their coding assistant.

Conclusion

The best LLM for coding tasks depends on your specific needs:

  • General Coding Assistance: GitHub Copilot and CodeWhisperer are excellent choices for real-time coding assistance in IDEs.
  • Open-Source Options: StarCoder, WizardCoder, and CodeGen are great open-source alternatives for developers who prefer flexibility and control.
  • Competitive Programming: AlphaCode excels at solving complex algorithmic challenges and is ideal for competitive programmers.
  • Proprietary Models: Codex and PaLM-Coder offer high-performance coding capabilities but may require API access or subscription.

By exploring these models, you can find the right tool to enhance your coding workflow, whether you're looking for real-time assistance, open-source flexibility, or advanced reasoning capabilities.