I Tried GitHub Copilot vs. ChatGPT for Coding: What I Learned

GitHub Copilot vs. ChatGPT choosing between them is like picking a travel guide vs. a GPS — both helpful, but for different kinds of coders. GitHub Copilot is like a travel guide already familiar with the road and shortcuts. It's ideal when you know where you are going and want to speed things up. 

On the other hand, ChatGPT is your GPS, giving you clear directions step-by-step and explaining the road ahead.

As a no-coder and a productivity geek, I spent weeks putting both tools to the test. To see how two popular AI tools stack up in real-life situations, I devised seven coding tasks: building a to-do list web app, fixing a JavaScript logical error, creating a personal portfolio landing page, implementing a search algorithm, developing a weather dashboard, generating inspirational quotes, and designing a color palette creator. 

These tasks focused on practical coding challenges and creative problem-solving. By putting them to the test across these tasks, we’ll explore which tools stand out as the best AI code generation software. 

To keep things fair, I gave both tools the same prompts, with no changes at all. My goal was simple: I wanted to find out which tool does a better job at what and who might benefit from using each one.

Here is what I found: GitHub Copilot shines at speeding up the coding process by offering smart autocomplete suggestions directly within the IDE. Meanwhile, ChatGPT excels at generating structured code and can also teach you how and where to use it while clarifying any doubts you might have.

Note: Both GitHub (a Microsoft subsidiary) and OpenAI frequently roll out new updates to these AI coding assistants. The details below reflect the most current capabilities as of June 2025 but may change over time.

GitHub Copilot vs. ChatGPT: What’s different and what’s not?

GitHub Copilot and ChatGPT are both some of the best AI coding assistants out there, but they serve very different roles in how you write, debug, and ship code. GitHub Copilot whispers suggestions directly into your IDE, while ChatGPT is your brainstorming partner in the chat window.

Recently, GitHub Copilot’s chatbot has expanded beyond OpenAI models to include other AI models, making it even more powerful. Let’s dig into how they compare and their shared strengths. 

GitHub Copilot vs. ChatGPT: The differences

GitHub Copilot is a focused coding tool inside your editor that allows you to complete code as you type. ChatGPT is a flexible AI assistant that helps with coding, planning, learning, and more. GitHub Copilot speeds things up, whereas ChatGPT explains and guides. Both are powerful, but built for different kinds of workflows.

• Primary use case:  GitHub Copilot is a specialized AI tool focused exclusively on code completion. It works inside your code editor, suggesting and completing code quickly based on your writing. This tool is designed for developers who want to code faster. On the other hand, ChatGPT is a versatile, general-purpose AI assistant designed to help with various tasks, including coding, planning, debugging, learning, and documentation. It is especially valuable for non-coders, solo developers, or anyone building projects who need detailed explanations, guidance, or brainstorming alongside coding support. GitHub Copilot allows advanced codex features only for paid users, while ChatGPT offers free tiers with coding support and additional capabilities in its paid plans.
• Learning and explainability:  Copilot doesn’t explain; it just completes. It is good if you already know what you are doing. ChatGPT can explain code line-by-line, generate tutorials, and even walk you through concepts with analogies.
• AI models and processing power: Both tools use advanced OpenAI models, but in different ways. GitHub Copilot is a fine-tuned variant of GPT-4 and also supports other models like Claude and Google’s Gemini 2.5 pro. ChatGPT Plus, on the other hand, gives you access to GPT-4o, a multimodal agent capable of complex reasoning, debugging, and file analysis.
• Context awareness: GitHub Copilot can work inside your IDE and pulls real-time context from the file you're editing and nearby code, making it sharper for inline suggestions and live coding help. ChatGPT can progress large chunks of code across multiple files or uploads, making it great for deep debugging, architecture reviews, and whole project reasoning if you feed the inputs manually. So, while Copilot feels more immediate and seamless during active development, ChatGPT offers a broader context.

GitHub Copilot vs. ChatGPT: Key similarities

Despite their different styles, these tools have a lot in common, and when used together, they can be surprisingly complementary. 

• Contextual code completion: Both can generate lines, functions, and code blocks that reduce manual typing and repetitive work.
• Multilingual programming support: Python, JavaScript, HTML, CSS, SQL, Go, and more. They both handle a wide range of modern programming languages.
• Productivity and learning: Whether you are building or troubleshooting, both tools help you write better code faster and learn as you go.
• Powered by Codex: Both GitHub Copilot and ChatGPT utilize OpenAI’s Codex. Which can perform a variety of developer-focused tasks for you, such as writing new features, answering questions about your codebase, fixing bugs, and even proposing pull requests for review. 

Disclaimer: AI responses may vary based on phrasing, session history, and system updates for the same prompts. These results reflect the models' capabilities at the time of testing.

GitHub Copilot vs. ChatGPT: How they actually performed in my tests 

If you are all the way here, I am guessing you are just as curious as I was to find out which tool came out on top. I will walk you through how I tested both tools, what the experience was like, and how I have broken down my verdict to make it easy (and hopefully fun) to follow.

• What stood out? I will highlight the strengths, weaknesses, and any surprises (good and bad) I noticed from both tools. 
• Who did it better? I will tell you which AI came out on top based on accuracy, creativity, efficiency, and how easy it was to use the output.
• Final verdict: I’ll share my honest take on which AI is a better choice for a particular task.

Ready? Let’s go!

1. To-do list web app

I wanted to build a simple to-do list web app to test how GitHub Copilot and ChatGPT handled everyday coding tasks.

GitHub Copilot surprised me with a sleek, minimal design. It automatically split the code into separate HTML, CSS, and JS files, making things much cleaner and easier to manage. The structured layout felt more maintainable in the long run. 

ChatGPT returned a neat single-file demo with colorful buttons and a friendly interface. However, I felt ChatGPT’s response, having all the HTML, CSS, and JavaScript bundled together, was a bit cluttered once I thought about extending the app later.

Winner: GitHub Copilot 

2. Personal portfolio landing page

Creating a portfolio is common for beginners who are working on real-world projects. I have wanted to build a portfolio site for myself, so this was a perfect opportunity to put my skills to the test. 

GitHub started strong, especially with CSS separated into its file for easier future updates. But compared to ChatGPT, Copilot's design felt simpler and lacked important features, like project cards and detailed navigation, elements that make a portfolio truly showcase your work and engage visitors.

ChatGPT's solution, on the other hand, felt smooth right from the start. Everything came out well, like displaying all sections, navigation, project cards, and the contact form — exactly as expected, without errors. Having project cards included was particularly helpful since portfolios typically need this feature.

Winner: ChatGPT

3. JavaScript logical error

For this test, I gave both tools a common JS bug, using the assignment operator (=) instead of the equality check (===) inside a conditional statement. This bug trips up many beginners, so I wanted to see not just if they could fix it but also how they explained the solution. 

GitHub Copilot’s fix was equally effective in solving the problem, but it just spotted the error and rectified it. I found the explanation a bit repetitive. As a beginner, I still wouldn’t have understood why the error happened without more context. 
So, in my case, I felt GitHub Copilot's explanation fell short. There was nothing technically wrong, but these minor distractions stood out.

ChatGPT’s correction felt smooth and concise. It quickly pinpointed the error and clearly explained why the bug happened, and immediately showed the corrected code. Then, it wrapped everything up with a one-line summary that even someone new to coding could follow. ChatGPT gave me both the what and why without overwhelming me.

ChatGPT's more precise explanation and straightforward presentation made it feel slightly easier to follow, especially for beginners looking for a straightforward answer.

Winner: ChatGPT 

4. Search algorithm

I asked both GitHub Copilot and ChatGPT to compare the implementation of the JavaScript binary search function to see which felt easier and more practical to use. Binary search is one of those foundational algorithms that every coder runs into at some point.

It's a fast way to find a specific item in a sorted list, something that comes up often in technical interviews and real-world projects. I wanted to see if they could write it correctly and how clearly they explained it.

GitHub Copilot offered a concise and efficient take on iterative binary search. The function was well-structured, and its brief inline comments conveyed its purpose. I liked how it delivered just what was needed, no extra content or prolonged explanations.  

In contrast, the ChatGPT solution was also correct and easy to follow. The inline comments were helpful, making the logic easy to understand quickly. However, I felt the explanation was overly extensive and created unnecessary scrolling when I just wanted a quick reference. 

Winner: GitHub Copilot

5. Weather dashboard

I wanted to build a small weather-themed UI as a beginner project, something simple, visual, and easy to customize later. I specified that the dashboard should show weather data for global locations, and asked for basic features like temperature, weather condition, and an icon representing the current weather.

Like all the other responses, GitHub Copilot put HTML, CSS, and JS in separate files. It felt way cleaner, especially when I wanted to change colors or fonts. The design also has a gradient background, and weather emojis make it feel more polished.

ChatGPT felt like opening a snack pack — just one HTML file to copy and open. It was easy to tweak, but finding style rules buried in the HTML was challenging. Still, it worked out of the box and didn’t break. The design was nice enough, with a pastel card layout that, while basic, looked decent. 

Winner: Split; GitHub Copilot made future edits way easier, while ChatGPT made it easy to set up with just one code.

6. Inspirational quote generator

This time, I just wanted the tools to say nice things to me! Testing quote generators sounded like a chill way to explore tools. One nailed the vibe; the other one needed a pep talk.

GitHub Copilot looked good with an orange gradient and strong shadows. Clicking worked well and added a nice fade effect, but sometimes, it repeated the exact quotes, which broke the experience a bit. So, for a beginner, ChatGPT made me smile faster.

ChatGPT was ready to go the moment I entered the prompt. There are no missing links or blank screens; it works immediately. I liked the styling; it was clean, with soft colors, round edges, and smooth transitions. Also, there is no repetition of quotes. 

Winner: ChatGPT

7. Color palette creator

After testing to-do lists, portfolios, and quote generation, I wanted to end with a little more fun: a color palette generator. I asked GitHub Copilot and ChatGPT to design a webpage that generates random aesthetic color palettes. 

GitHub Copilot's color palette was more monochrome than just random colors. This gave its output a sense of harmony as if the colors belonged to a theme or brand board rather than a truly random set. The background was also a calming green; the extra details made it feel more like a finished tool than a demo.

ChatGPT's five color swatches looked nice. Each swatch had its HEX code clearly displayed, and clicking one instantly triggered a slick confirmation message — “#HEX copied!” — that appeared at the center of the page. It is great for quick use or showing a friend. 

Winner: GitHub Copilot 

Here’s a table showing which chatbot won the tasks.  

Key insights on GitHub Copilot vs. ChatGPT from G2 Data

I also looked at review data on G2 to find strengths and adoption patterns for GitHub Copilot and ChatGPT. Here's what stood out:

Satisfaction ratings:

• GitHub Copilot ranks high in product direction (9.9), ease of setup (9.3), and ease of doing business (9.2).
• ChatGPT excels in ease of use (9.6), ease of setup (9.6), and ease of doing business (9.5).

Top industries represented:

• GitHub Copilot has a stronger presence in computer software, IT, financial services, computer and network security, and telecommunications.
• ChatGPT dominates computer software, IT services, marketing, financial services, and education management.

Highest-rated features:

• GitHub Copilot stands out for code quality (88%), documentation (88%), input processing (87%), and interface (86%).
• ChatGPT excels in interface (94%), user interaction learning (90%), understanding (90%), and natural conversation (90%).

Lowest-rated features:

• GitHub Copilot struggles with updating schedule (84%), community (84%), and accuracy (85%).
• ChatGPT struggles with data security (82%), error learning (83%), content accuracy (83%), and community (83%).

Frequently asked questions on GitHub Copilot and ChatGPT

Got more questions? Get the answers here!

Q1. GitHub Copilot vs. ChatGPT: Which is better?

It boils down to what you need. If you spend most of your time writing code inside an editor and want instant inline suggestions, then GitHub Copilot is your tool. But if you are juggling everything from brainstorming to documentation to debugging explanations, ChatGPT is more of an all-rounder. 

Q2. GitHub Copilot vs. ChatGPT: Which one should I buy for coding purposes?

GitHub Copilot (Individual) is $10/month and gives unlimited code completions, chat features, and premium model access. It works perfectly with VS Code, JetBrains, etc. ChatGPT costs $20/month and unlocks GPT-4, which gives faster responses, plugins, file uploads, image/audio support, and code help. 

Q3. Can GitHub Copilot generate documentation or comments for my code?

Yes! GitHub Copilot can suggest comments and documentation based on your code or prompts, helping you write more precise explanations and improve code readability.

Q4. What is better for fixing or writing code? GitHub Copilot vs. ChatGPT?

GitHub Copilot shines with one-line or whole-function suggestions as you type. ChatGPT’s conversational style lets you paste error messages or snippets and get step-by-step explanations or rewrite suggestions.

Q5. Is GitHub Copilot free?

GitHub Copilot offers a free trial but requires a paid subscription for continued use. There are free options for verified students and trainers of popular open-source projects.

Q6. How to use GitHub Copilot?

Install the GitHub Copilot extensions in your code editor (like Visual Studio Code), sign in with your GitHub Copilot account, and start coding. Copilot will suggest completions and snippets as you type.

Q7. GitHub Copilot vs. ChatGPT: Which has better integration?

GitHub Copilot is native to major IDEs like VS Code, Visual Studio, JetBrains, and Neovim. GitHub.com suggestions drop right into your editor; you don't need to do any extra setup once you install the plugin. ChatGPT hooks in via community or official extensions, but it feels more like a side-panel chat than built-in.  

Q8. Can I use both GitHub Copilot and ChatGPT?

Absolutely. Many developers keep Copilot in the editor for live completions and open ChatGPT for more profound questions.

Q9. GitHub Copilot vs. ChatGPT: Which is best for basic coders to learn?

Copilot assumes that you already know what you are doing, and it knows where to drop code and what you want next, which can be opaque if you are still learning the ropes. Beginners often find ChatGPT more approachable because of its natural language Q&A style, which feels like asking a tutor. 

Q10. How to use GitHub Copilot in Visual Studio?

To use GitHub Copilot in Visual Studio, first, install the GitHub Copilot extension from Visual Studio Marketplace. Then, sign in with your GitHub Copilot account, and you will start getting AI-powered code suggestions as you type. You can accept, reject, or modify the suggestions easily within your editor.

Q11. Can GitHub Copilot replace ChatGPT?

No, not wholly; GitHub Coiplot focuses on code generation and suggestions inside your editor. ChatGPT offers broader conversational abilities, including explaining concepts, writing code snippets, debugging help, and general problem-solving. They complement rather than replace each other.

Q12. GitHub Copilot vs. ChatGPT: How do they differ in functionality?

GitHub Copilot is AI-driven code completion and refactoring inside your IDE. Think “autocomplete on steroids” plus a mini chat for quick code tweaks. ChatGPT is a conversational AI that can generate and explain code, draft emails, write tests, analyze data, brainstorm, and basically do anything text-oriented, not just code.

GitHub Copilot vs. ChatGPT: My final verdict

After testing seven real-world samples, I found that GitHub Copilot excelled in three tasks, while ChatGPT came ahead in another three. One task showed mixed results where both tools performed comparably.  These tools excel in different ways for different types of coders. GitHub Copilot stood out when it came to tasks requiring clean file separation, modular code structure, and being developer-friendly. If you are coding inside an IDE and looking for a quiet, sharp AI partner that complements your workflow, GitHub Copilot is your tool. 

ChatGPT, on the other hand, shone in quick wins, especially for beginners. It often felt more immediately rewarding. It delivered satisfying results with minimal setup, which made it feel more approachable. Use ChatGPT if you are early in your coding journey and want something quickly that works now with no setup stress.

And honestly? The real power comes from using both together. Because in this AI-ruling world, the best coder is not the one who just picks one tool, but the one who knows how to wield the strengths of both.