Top LLMs for Coding All Developers Should Know About

The landscape of programming is changing because the best LLMs for coding have changed how developers write, debug, and optimize code. LLMs are capable of doing everything from accelerating routine programming chores to writing entire functions for developers.

However, given the large number of available models, how can you choose which is the best LLM for coding? What should developers look for when choosing an LLM to help with their programming tasks?

In this article, we will examine the best LLM for programming available. We will also explore the developer benefits of these models, focus on their pros and cons, and suggest how you can incorporate LLMs into your development flow.

If you’re new to programming or have some experience as a developer, learning what you can do with LLMs will make your coding easier and more satisfying!

What Is an LLM for Coding?

Large Language Models (LLMs) are a type of artificial intelligence that can understand and generate human-like text based on the data they’ve been trained on. There are LLMs intended for code generation, and programming-specific LLMs can help developers with a multitude of programming tasks.

These models are trained on vast amounts of code from different programming languages and can write new code, explain existing code, and even debug errors.

An LLM for coding is nothing but a tool that developers integrate into their workflow. To be more practical, it generates code for you, helps you with syntax suggestions, or explains any complex function. The most sophisticated models also flag bugs and can point out where optimizations must be added.

Why Are LLMs Important for Developers?

1. Increased Efficiency

LLMs allow developers to focus on more strategic tasks by handling repetitive coding operations. Whether it’s generating boilerplate code or completing functions based on a few instructions, LLMs drastically reduce the time it takes to write and debug code.

2. Improved Accuracy

LLMs reduce human errors, especially in syntax-heavy programming languages like Python, Java, or C++. By providing real-time suggestions and syntax corrections, LLMs can help developers avoid common coding mistakes.

3. Enhanced Learning and Documentation

For new programmers, LLMs can act as real-time tutors. They can explain code in simple terms, helping developers understand how different functions work. Additionally, these models can generate documentation, which is crucial for team projects and maintaining clean, understandable code.

4. Better Collaboration

Teams using LLMs for coding can achieve better collaboration as these models help maintain coding standards across different members. By generating uniform code and offering consistent suggestions, LLMs ensure that everyone on the team writes cleaner, more maintainable code.

The Best LLMs for Coding

1. OpenAI Codex

OpenAI Codex is one of the most well-known LLMs for coding and powers GitHub Copilot, a widely-used AI coding assistant. Trained on large amounts of open-source code, Codex supports dozens of programming languages, including Python, JavaScript, Ruby, and Go.

Key Features:

• Code Generation: Codex can generate entire functions or snippets based on natural language prompts.
• Autocomplete and Syntax Suggestions: It provides real-time syntax corrections and code completion, reducing the chances of syntax errors.
• Debugging: Codex can identify issues in code and suggest fixes, helping developers troubleshoot errors faster.

Supported Languages: Python, JavaScript, Java, Ruby, PHP, Go, and more.

Why It’s Great:
Codex integrates seamlessly with GitHub Copilot, making it an excellent choice for developers who use GitHub as part of their workflow. The model is particularly strong when it comes to code generation and debugging, making it one of the top LLMs for developers.

2. GPT-4

GPT-4, developed by OpenAI, is a versatile LLM capable of handling a wide range of tasks, including coding. Although it wasn’t designed exclusively for coding, GPT-4 excels at code generation, explaining complex algorithms, and offering programming suggestions in response to natural language queries.

Key Features:

• Code and Explanation Generation: GPT-4 can write new code from scratch and explain how existing code works, making it useful for both experienced developers and beginners.
• Natural Language Understanding: It can respond to natural language queries, which is helpful for developers looking for quick explanations or help with unfamiliar functions.
• Debugging Assistance: GPT-4 helps identify bugs in code and suggests potential solutions, though its debugging capabilities are slightly less specialized than Codex.

Supported Languages: Python, JavaScript, C++, Java, HTML, and more.

Why It’s Great:
GPT-4 offers excellent flexibility, capable of helping with both code generation and learning. For developers who need a more generalized tool that can also code, GPT-4 is a great option, and it’s one of the best LLMs for developers looking for versatility.

3. GitHub Copilot

GitHub Copilot, powered by OpenAI’s Codex, has quickly become one of the most popular LLMs for developers.

Seamlessly integrated into IDEs like Visual Studio Code, GitHub Copilot assists developers with real-time code suggestions, auto-completion, and even debugging. This tool enables developers to focus on logic while automating boilerplate code generation.

Key Features:

• Intelligent Code Completion: Suggests code snippets as you type, minimizing repetitive coding tasks.
• Copilot Chat: Provides a conversational interface where developers can ask for code explanations, get debugging advice, and more.

Supported Languages: Python, JavaScript, TypeScript, Ruby, Java, and others.
Token Size: 4,096
Why It’s Great: Copilot integrates directly into your favorite coding environment, speeding up the development process with real-time intelligent code suggestions.

4. Llama 3

Llama 3 is the latest release from Meta AI, known for its advanced reasoning and code generation capabilities. This model is ideal for developers working on large, complex projects thanks to its ability to handle extensive context.

Key Features:

• Improved Code Generation: Llama 3 excels at generating and completing code across multiple languages.
• Reasoning and Debugging: Its enhanced reasoning skills make it great for complex problem-solving and debugging.

Supported Languages: Python, C++, Java, and others.
Token Size: 8,192
Why It’s Great: Llama 3 is perfect for large-scale projects, offering enhanced reasoning capabilities and a strong ability to handle larger codebases.

5. TabNine

TabNine is an AI-powered code completion tool that integrates with popular code editors like Visual Studio Code, JetBrains, and Sublime Text.

While it may not be as widely recognized as Codex or GPT-4, TabNine is designed to make coding faster and more efficient by predicting and completing code in real time.

Key Features:

• Code Autocompletion: TabNine provides fast, intelligent code autocompletion, predicting what you’re about to write and suggesting the next part of the code.
• Lightweight and Fast: TabNine runs locally or in the cloud, making it lightweight and ideal for developers who want speed without sacrificing functionality.
• Context-Aware Suggestions: It learns from your coding patterns, offering personalized suggestions based on your previous coding behavior.

Supported Languages: Python, JavaScript, TypeScript, Go, Java, Rust, and more.

Why It’s Great:
TabNine’s strength lies in its ability to speed up coding by providing highly accurate autocompletion. It’s a great tool for developers who want minimal disruptions in their coding process.

6. Replit’s Ghostwriter

Replit’s Ghostwriter is a relatively new tool but gaining popularity due to its seamless integration with Replit’s online IDE. Ghostwriter acts as a coding assistant that helps users write, fix, and improve their code in real time.

Key Features:

• Instant Code Suggestions: Ghostwriter provides real-time code suggestions as you type, speeding up development.
• Bug Fixing: It identifies common bugs and suggests fixes to improve the code.
• Code Explanation: Ghostwriter can explain what different parts of the code do, making it helpful for learning and troubleshooting.

Supported Languages: Python, JavaScript, HTML/CSS, SQL, and more.

Why It’s Great:
Ghostwriter is perfect for beginners or developers who are looking for a hands-on assistant that works directly in their browser. For those using Replit, this is one of the top LLMs for coding with tight integration into an IDE.

7. Amazon CodeWhisperer

Amazon CodeWhisperer is a powerful AI code generation tool designed to integrate directly with AWS (Amazon Web Services). It assists developers by suggesting code snippets in real time, reducing the time needed to write cloud applications.

Key Features:

• Cloud-Based Code Generation: CodeWhisperer specializes in generating code tailored for AWS cloud applications.
• Security Features: It suggests best practices for coding securely in the cloud, ensuring that the generated code meets security standards.
• Multi-Language Support: CodeWhisperer works with multiple programming languages, making it versatile for cloud development.

Supported Languages: Python, Java, JavaScript, and more.

Why It’s Great:
For developers building applications on AWS, CodeWhisperer offers specialized knowledge and tailored suggestions, making it one of the best LLMs for developers focused on cloud computing.

8. Claude 3 Opus

Claude 3 Opus stands out with its massive token size and advanced reasoning capabilities. This model is designed to handle multimodal tasks, making it suitable for developers working on extensive projects requiring simultaneous code and text processing.

Key Features:

• Multimodal Support: Handles both code and text for a more comprehensive development experience.
• Advanced Debugging: Excellent for identifying and resolving complex issues in the code.

Supported Languages: Python, JavaScript, Go, and more.
Token Size: 200,000
Why It’s Great: Claude 3 Opus is designed for developers handling large-scale projects, thanks to its unparalleled token size and robust debugging features.

9. CodeQwen1.5

CodeQwen1.5 is a versatile model supporting over 92 languages, making it one of the top LLM for coding available. Its long-context understanding and basic code generation features make it ideal for developers working with diverse programming languages.

Key Features:

• Multilingual Support: Works with over 92 programming languages, making it a highly adaptable tool for global development teams.
• Long-Context Understanding: Ideal for developers working on large or complex codebases.

Supported Languages: Python, Java, C++, and others.
Token Size: 64,000
Why It’s Great: CodeQwen1.5 offers excellent long-context handling and is perfect for developers who work across multiple programming languages.

10. Code Llama

Code Llama is Meta’s specialized tool for code generation and debugging, with an impressive token size for handling large-scale coding projects. Its support for multiple languages and strong debugging capabilities make it a top choice for developers.

Key Features:

• Code Generation and Debugging: Provides detailed suggestions for improving and fixing code.
• Large Token Capacity: Handles extensive projects without losing track of the context.

Supported Languages: Python, C++, Java, and more.
Token Size: 100,000
Why It’s Great: Code Llama is great for developers working on large, complex codebases and who need robust code generation and debugging support.

11. Falcon 40B

While Falcon 40B focuses more on natural language generation, its support for multiple programming languages makes it a capable tool for developers interested in coding tasks that also require natural language interaction.

Key Features:

• Multilingual Support: Capable of handling multiple programming languages while offering natural language processing capabilities.
• Natural Language Generation: Focuses on generating human-like text, useful for writing comments, documentation, or user instructions in code.

Supported Languages: Python, JavaScript, and others.
Token Size: N/A
Why It’s Great: For developers who need to generate both code and natural language text, Falcon 40B offers a versatile solution.

12. Ernie

One of the best LLMs for coding is Ernie! It is a unique model offering bilingual support for both Chinese and English. It excels in multimodal generation and natural language understanding, making it a great tool for developers working on bilingual projects.

Key Features:

• Bilingual Capabilities: Ideal for developers working in both English and Chinese environments.
• Multimodal Support: Capable of handling code and text generation.

13. Mistral

Mistral focuses on multilingual capabilities and offers advanced function calling. It’s designed for developers who need a more precise, detailed approach to code generation and debugging, especially in multi-language environments.

Key Features:

• Multilingual Support: Works across various programming languages.
• Advanced Function Calling: Helps developers with complex code execution and troubleshooting.

Supported Languages: Python, Java, C++, and more.
Token Size: 128,000
Why It’s Great: Mistral’s multilingual capabilities and advanced function handling make it perfect for developers working in diverse coding environments.

14. Orca

Orca is a top LLM for developers known for its focus on progressive learning and enhanced reasoning abilities. With a moderate token size, it is well-suited for developers looking for tools that improve code accuracy and offer incremental learning based on usage patterns.

Key Features:

• Enhanced Reasoning: Orca’s progressive learning capabilities enable it to adapt to the developer’s coding style over time.
• Contextual Learning: Orca improves its code suggestions as it learns from prior inputs.

Supported Languages: Python, JavaScript, and others.
Token Size: 13,000
Why It’s Great: Orca is ideal for developers who want a coding tool that learns and adapts to their style, offering better code suggestions over time.

15. PaLM

Palm focuses on advanced reasoning and debugging capabilities, making it a strong contender for developers who need help with complex problem-solving tasks. Its moderate token size allows it to handle larger projects without losing track of the coding context.

Key Features:

• Advanced Debugging: Helps resolve issues efficiently and provides reasoning behind coding suggestions.
• Multilingual Support: Works across multiple programming languages.

Supported Languages: Python, C++, Java, and more.
Token Size: 8,000
Why It’s Great: Palm’s combination of advanced reasoning and debugging makes it perfect for developers handling challenging, large-scale projects.

16. Gemma

Gemma offers an easy-to-use interface for code generation and debugging, making it one of the best LLMs for coding. With a focus on Python and JavaScript, Gemma is ideal for web and backend developers who need real-time assistance.

Key Features:

• Code Generation: Helps generate and troubleshoot code in real time.
• Debugging Support: Offers solutions to fix issues quickly.

How to Choose the Best LLM for Coding

When selecting the best LLM for coding, it’s essential to consider your unique needs and workflow. Here are a few factors to keep in mind:

1. Programming Language Support

Make sure the LLM supports the programming languages you use most frequently. Codex, GPT-4, and TabNine support multiple languages, making them great all-around tools, while CodeWhisperer is ideal for cloud developers working in the AWS ecosystem.

2. Ease of Integration

If you’re using specific code editors like VS Code or JetBrains, TabNine integrates smoothly, while Codex powers GitHub Copilot, which integrates well with GitHub users.

3. Debugging and Troubleshooting

If debugging is a significant part of your workflow, LLMs like Codex and Replit Ghostwriter offer built-in error detection and debugging suggestions.

4. Learning and Collaboration

For developers who want to learn new skills or collaborate in team environments, GPT-4 and Ghostwriter are excellent options for generating explanations, documentation, and code comments.

The Bottom Line

Large Language Models are revolutionizing the way developers write code, offering powerful tools to automate tasks, improve accuracy, and increase productivity.

Among the best LLMs for coding, OpenAI Codex, GPT-4, and TabNine stand out for their versatility, ease of use, and powerful features. Meanwhile, Amazon CodeWhisperer is perfect for developers working in cloud environments, and Replit’s Ghostwriter is an excellent choice for those who prefer browser-based coding tools.

As LLM technology continues to evolve, these tools will only become more integrated into the daily workflows of developers, making coding faster, smarter, and more accessible to all.