GitHub Copilot vs. ChatGPT: Ultimate AI App Comparison

GitHub Copilot and ChatGPT are both leading generative AI applications and are similar to one another in important ways. Yet, there are also crucial differences between them, especially when it comes to the depth and breadth of their text-based and code-based content creation capabilities.
Which generative AI platform is best for your needs? We’ll take a closer look at each of these tools across a few key metrics, but first here’s a quick summary of their individual strengths:
 

GitHub Copilot: Best for the range and sophistication of its coding features and developer tools. Compared to ChatGPT, this solution offers in-depth expertise in coding and programming, particularly for code completion, code snippets, and in-depth support in your preferred coding environments.
ChatGPT: Best for all-purpose content generation and more basic coding support. Compared to GitHub Copilot, ChatGPT is a more accessible tool that not only can support straightforward coding scenarios but can also generate text, images, and other forms of content, depending on user inputs and plan subscriptions.

To better understand which generative AI solution is best for your purposes, we’ll dig further into the similarities and differences across a range of different criteria below.

TABLE OF CONTENTS
ToggleGitHub Copilot vs. ChatGPT at a GlanceWhat Is GitHub Copilot?What Is ChatGPT?Best for Pricing: It DependsBest for Core Features: It’s a TieBest for Chatbot Functions: ChatGPTBest for Output Accuracy and Relevance: It DependsBest for Coding Capabilities: GitHub CopilotBest for Ease of Use: ChatGPTWhy Shouldn’t You Use GitHub Copilot or ChatGPT?If GitHub Copilot or ChatGPT Isn’t Ideal For You, Check Out These AlternativesReview MethodologyBottom Line: GitHub Copilot vs. ChatGPT

GitHub Copilot vs. ChatGPT at a Glance

Pricing
Chatbot Functions
Output Accuracy and Relevance
Coding Capabilities
Ease of Use

GitHub Copilot

Dependent on
Use Case

Dependent on
Use Case
Best

ChatGPT
Dependent on
Use Case
Best
Dependent on
Use Case

Best

What Is GitHub Copilot?
GitHub Copilot is a generative artificial intelligence coding assistant supported by GitHub, whose user base counts more than 100 million developers, more than 400 million open-source contributions, and about 500 languages to build software (JavaScript is the most popular).
This cloud-based artificial intelligence tool was developed by GitHub and OpenAI to assist users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs). With this integration and focused features, GitHub Copilot supports users in writing faster code with less work. Copilot draws context from comments and code to suggest individual lines and whole functions instantly.

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Key Features of GitHub Copilot
GitHub Copilot provides users with a range of beneficial coding features, including the following:

Built-in security and quality assurance features: To adhere to an organization’s privacy and security expectations, GitHub Copilot includes various enterprise-level security features, including a built-in vulnerability prevention system that blocks insecure coding patterns, the option to fine-tune private copilots, IP indemnity, and a security vulnerability filter.
Natural-language-powered coding assistant: Though its outputs and main purposes are focused on code, users of all skill levels can input natural language prompts and questions to generate new code, complete code, or troubleshoot existing code.
Integration with organizational documentation and ecosystems: GitHub Copilot smoothly integrates with multiple IDEs, it can be used from the CLI, and it contextualizes its responses based on an organization’s relevant documentation and style conventions.

With a chatbot-like, natural language approach, GitHub Copilot’s coding assistant can quickly generate large quantities of relevant code and explain its choices to users in real time. Source: GitHub.
Pros

Integrates with existing coding ecosystems and resources.
Built-in vulnerability prevention system.

Cons

Limited chatbot capabilities for non-programming questions.
Occasional coding errors, especially with undivided code segments.

What Is ChatGPT?
ChatGPT is a generative AI tool developed by OpenAI and powered by its large language models (LLMs), GPT-3.5 or GPT-4, depending on your chosen plan. The model was trained on massive amounts of text data from the internet and other credible sources, which enables it to generate human-like text responses to a given prompt.
It answers questions, converses with users on a variety of topics, and even generates creative writing pieces, images, and some code. As such, ChatGPT goes far beyond the capabilities of a typical chatbot to solve problems and answer questions with logic, intelligence, and strategy.
GPT is an abbreviation for generative pre-trained transformer, a form of advanced artificial intelligence (AI). ChatGPT simulates human thought by using a neural network machine learning model trained based on a vast trove of data and complex algorithms.

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Key Features of ChatGPT
ChatGPT users can take advantage of a wide range of generative AI and content generation features, including the following:

Plaintext prompting: Users do not have to have any coding or special knowledge to use ChatGPT. With the simplest of natural language inputs, users can generate complex text, image, and code outputs.
Multimodal content outputs: ChatGPT is designed for various types of content generation, though its free version is a little more limited. Interested users can generate text, code, and image content (with the help of DALL-E, another OpenAI tool).
Code snippets and explanations: Though ChatGPT is not primarily a coding tool, it does an effective job of handling basic code completion and code snippet creation tasks. Additionally, it offers detailed explanations and information on use cases to help users move forward, regardless of their technical skills and knowledge.

Acting as a user with little to no experience with coding or programming, I asked ChatGPT a simple question in order to generate a code snippet. In addition to the example code snippet, ChatGPT offered a detailed explanation of the snippet’s purpose and how it can be used. Source: Shelby Hiter via ChatGPT.
Pros

Multipurpose uses and capabilities.
Easy to access and use for all skill levels.

Cons

Limited coding and image capabilities in the free plan.
Limited coding features compared to GitHub Copilot.

Best for Pricing: It Depends
The best solution based on pricing depends on your particular requirements. For users who need a free, limited tool, ChatGPT is the more affordable solution; but for users who need an affordable and accessible paid plan with more robust features, GitHub Copilot offers more affordable paid plans.
Pricing for ChatGPT all depends on which plan you select. The tool is available in a free plan that supports unlimited messages, interactions, and chat history, but it is still limited in areas like speed, context windows, and multimodality because it runs on GPT-3.5 rather than GPT-4. Paid plans that offer more extensive functionality are available at $20 per user per month, $25 per user per month, and undisclosed enterprise pricing. Those subscribing gain access to ChatGPT at peak times, faster responses, and priority access to new features and improvements.
In contrast, there is not a free version of GitHub Copilot that users can access. However, its paid plans start at more affordable rates, with Copilot Individual coming in at $10 per month, Copilot Business priced at $19 per user per month, and Copilot Enterprise available at $39 per user per month.
In summary, the best choice for affordable pricing depends on what you need the tool for, how many users you have, and how you plan to scale in the future.
Best for Core Features: It’s a Tie
Because GitHub Copilot and ChatGPT serve the needs of such different users and audiences, the range and quality of their core features give them an equal score here.
ChatGPT offers a wider range of content generation options, with users able to generate longform and shortform text, images (via the DALL-E integration), and basic code segments. The tool is easy to use and allows users to input their queries in natural language and plaintext. They can also easily access this tool on either mobile applications or the web with continuity between the different interfaces.
GitHub Copilot offers a smaller range of possible content outputs, focusing almost entirely on code generation with natural language explanations and recommendations. Because it also takes a natural-language prompting approach it is fairly easy to use, especially for experienced developers. It also integrates effectively with several IDEs, the CLI, and commonly used business applications and developer tools.
It’s difficult to compare these tools based on their core features because they have entirely different areas of focus, but they both do a good job of serving the needs of their core users.
Best for Chatbot Functions: ChatGPT
ChatGPT is the clear winner for chatbot capabilities.
ChatGPT is used as the “engine” in various chatbot applications to automate customer service, answer FAQs, and engage in conversation with users. It can respond conversationally by tapping into a comprehensive set of online text written by actual people, as well as news items, novels, websites, and more.
ChatGPT does a good job of analyzing information, evaluating online behavior, and even making product recommendations as part of the online sales and upselling process. Automation features extend to appointment scheduling, reservations, payment processing, queries about shipping schedules, order progress, product returns, product and service availability, and more with a high level of accuracy. Within the standalone ChatGPT interface, natural language Q&A is possible on a wide variety of topics, extending into longform storytelling and content generation.
ChatGPT can also do image interpretation using multimodal language AI models. This enables it to build websites based on sketches or suggest recipes based on a photo of what is in the fridge or sitting on a countertop.
Furthermore, ChatGPT can perform complex tasks. It has achieved some success with basic computer programming duties, but it ventures well beyond that into territory such as drawing up simple lawsuits, creating elementary computer games, passing exams, checking for plagiarism, generating written content, summarizing documentation, highlighting key passages within a text, and translating content into dozens of languages.
GitHub Copilot doesn’t do any of this, but it isn’t designed to. Rather than trying to be everything ChatGPT attempts to be, GitHub Copilot focuses — deeply and effectively — on its role as an AI assistant for software coding. However, it’s important to note that this AI assistant interface works similarly to a chatbot, as users can request code improvements, completions, and more in a chatbot interface with natural language.
Overall, ChatGPT is a much better chatbot solution. While GitHub Copilot has some very basic chatbot capabilities and features, it is not an important part of its design or product goals.
Best for Output Accuracy and Relevance: It Depends
The best solution between ChatGPT and GitHub Copilot for accuracy and relevant outputs is a toss-up. It all depends on what type of content you’re trying to generate.
ChatGPT can be prone to error, based on assumptions it makes on data that may not be current — ChatGPT cannot access real-time data when giving responses and is limited to its most recent knowledge base update. However, despite this limitation, possible hallucinations, and other minor errors, ChatGPT fairly consistently produces accurate and relevant outputs.
Previously, ChatGPT got into hot water with a few strange responses to queries and several completely wrong answers. Fortunately, each new version gets better, and GPT-4 has added a greater degree of accuracy.
OpenAI stated that GPT-4 is 82% less likely to respond to requests for content that OpenAI does not allow and 60% less likely to invent answers. But don’t expect it to be perfect, including with coding tasks. Its programming outputs should always be verified by human eyes.
GitHub Copilot similarly has some accuracy issues. Users accept on average 26% of all completions shown by GitHub Copilot. In certain languages, like Python, that goes up to 40%.
In other words, GitHub Copilot does not generate perfect code. Instead, it creates the best code possible given the context it has access to. Thus, code may not always work. At times, Copilot may rely on old or deprecated libraries and languages as well.
More common languages like Python, JavaScript, TypeScript, and Go tend to perform better compared to other programming languages. Additionally, GitHub Copilot is said to increase in accuracy when code is split into smaller functions, when meaningful names are used for function parameters, and when good instructions are given. Any code suggested by GitHub Copilot should be carefully tested, reviewed, and vetted. That said, it is typically better-quality code than the code generated by ChatGPT.
Both ChatGPT and GitHub Copilot produce occasional errors and poor assumptions, but with each iteration of training that they’ve received, they’ve both improved. In short, the best tool for output accuracy and relevance depends on what you need a generative AI tool to do, whether that’s coding or text generation.
Best for Coding Capabilities: GitHub Copilot
GitHub Copilot is a better solution than ChatGPT for most coding and programming use cases.
In general, GitHub Copilot produces more accurate code outputs, code completions, code snippets, and specific coding requests. It also offers more contextualized information about why certain coding decisions were made.
As an additional bonus for developers and programmers, GitHub Copilot is specifically designed with their needs and coding environments in mind. Instead of having to toggle back and forth between Copilot and a separate environment, Copilot works directly in CLIs and via other integrations for tools like VS Code, Visual Studio, Neovim, and JetBrains IDEs.
ChatGPT, while able to handle some basic coding requests, is a more general tool with less complex dedication to coding questions and projects. This means that it can handle several code completion and snippet generation tasks well, and it’s even pretty impressive compared to competitors when it comes to in-depth explanations, but it is not necessarily the best solution for coding projects with longer context windows, real-time content generation requirements, advanced troubleshooting, and other more intricate coding goals. It also does not necessarily produce as many accurate code responses, as ChatGPT was not specifically trained on code data and contextual awareness as Copilot was.
ChatGPT comes out of the open-source community. It can be plugged into other applications to generate responses via an API. Plugins are becoming available, including those for the likes of Kayak, Expedia, OpenTable, Slack, and Shopify, with more on the way. It is also integrated with many different programming languages.
GitHub Copilot is well-integrated with the IDEs mentioned above and can analyze and pull from billions of lines of code in multiple languages. Note, though, that it is trained on publicly available code. Brand new libraries, frameworks, and APIs are less integrated (and coding accuracy will be lower) as less public code is available for the model to learn from. It takes time for the GitHub Copilot codebase to build up enough examples to provide accurate code.
Generally speaking, GitHub Copilot is a better coding tool, both for its robust range and quality of coding capabilities as well as for its availability in typical developer environments.
Best for Ease of Use: ChatGPT
For most users, ChatGPT is easier to use and access than GitHub Copilot.
ChatGPT offers a user-friendly interface that can be directly accessed from the OpenAI website or via its well-reviewed and easy-to-use mobile apps for Android and iOS. Either free plan or paid plan users can use the tool from these different interfaces, and what’s more, users can maintain their conversational history and continuity across all of these versions. This tool does a great job of offering users a novice-friendly, plaintext approach to coding and other types of content generation, which makes it a great starter tool for new developers and basic problem-solving.
As far as its user interface goes, GitHub Copilot is user-friendly for users who have experience with GitHub and a developer-centric interface. However, for less technical users, the open-source community and coding-focused tool can be overwhelming and come with a higher learning curve than ChatGPT. This tool enables users to input plaintext prompts as well, but without some basic coding knowledge, it will likely be difficult to decipher GitHub Copilot’s responses.
Additionally, at this time, GitHub Copilot access options are fairly limited. The solution is almost entirely confined to a handful of IDEs and a very limited web version of the tool, though the vendor has announced that Copilot capabilities are coming to GitHub Mobile soon. Regardless, there is no free version of this tool, though Copilot Individual users can test it out with a free trial.
For both user-friendliness and accessibility, ChatGPT takes the lead. However, it’s important to note that GitHub’s open-source community can be a wealth of information for troubleshooting and learning how to use Copilot more effectively.
Why Shouldn’t You Use GitHub Copilot or ChatGPT?
GitHub Copilot and ChatGPT are both generative AI leaders for a reason, as they each offer accessible and high-powered solutions for a variety of casual and enterprise AI use cases. However, each tool has its weaknesses, shortcomings, and other reasons why you may want to find an alternative option:
Who Shouldn’t Use GitHub Copilot

Users looking for a free AI coding assistant.
Users who want multimodal content outputs that go beyond coding and programming use cases.
Users who aren’t part of or interested in the GitHub community.
Beginning coders and programmers who only need basic support.
Users who aren’t willing or able to quality-check Copilot’s outputs.

Who Shouldn’t Use ChatGPT

Users who need high-powered coding support.
Users who need real-time, consistently updated information.
Users who want a generative AI tool that integrates directly with their IDEs and other business tools.
Experienced programmers who need support with complex coding projects.
Users who aren’t willing or able to quality-check ChatGPT’s outputs.

If GitHub Copilot or ChatGPT Isn’t Ideal For You, Check Out These Alternatives

Gemini
Gemini is Google’s version of a multimodal generative AI solution that directly competes against ChatGPT and handles coding tasks in similar ways. It offers support for multiple programming languages, contextual awareness, support for debugging, and awareness of different technical documentation and concepts. It also is directly connected to Google’s search engine and internet capabilities, so it can give users real-time, updated data based on online sources of information.

Tabnine
Tabnine is a generative AI coding assistant that offers many similar features to GitHub Copilot, including the ability to integrate its features in your selected IDE and enterprise security and privacy features. Unlike GitHub Copilot, Tabnine also offers a free plan option. This plan includes basic AI code completion abilities, airgapped privacy and security, and access to community support.
Review Methodology
For this comparison of GitHub Copilot and ChatGPT, we focused on four core review criteria that are important to generative AI users, both for general use and specialized use cases. The criteria percentages listed below represent how we weighted the importance of each one for the total score each product received.
Depth of Core Features – 30%
To meet the complex needs of both developers and casual users, we assessed both of these tools in terms of the depth of the core features they offered. We paid special attention to output accuracy and relevance, context windows, training history and up-to-date knowledge, continuity, security and privacy features, usability of natural language interfaces, and more for this category.
Breadth of Core Features – 30%
Because both casual and professional users look to these tools for support, we also paid attention to the variety of features these tools offered. We specifically looked for multimodal capabilities, common enterprise and personal use cases discussed in user reviews, and unique features not offered by the competitor.
Accessibility – 20%
A generative AI tool is only as useful as it is accessible. This is why we reviewed both of these tools in terms of their accessibility, including ease of use, natural-language features, affordability (both for low-tier and high-tier packages), and integrations with other relevant business applications and tools. We emphasized the availability of these tools in multiple interfaces and formats as well.
Accuracy and Relevance – 20%
Particularly when producing code in commercial settings, accuracy and output relevance are high priorities. That is why we looked at both of these tools and considered how accurate and consistent their outputs are, how well they support quality assurance and troubleshooting tasks, and how effectively they handle contextualized requests.
Bottom Line: GitHub Copilot vs. ChatGPT
ChatGPT may be the better option for beginning coders and those who rarely code and aren’t part of the GitHub community. GitHub Copilot effectively aids developers in writing code faster and was designed 100% with code generation in mind. While ChatGPT can play a role in streamlining the development process, it is better as a broader AI system that incorporates multimodal content output and chat with some basic coding abilities.
In short, ChatGPT is more versatile as an overall generative AI solution to create content of all kinds, including software code. But GitHub Copilot is a far more powerful platform for developing software code. In either case, though, think of them as AI assistants to developers and content creators and not a replacement. Human minds remain an essential element of content creation and programming alike.
To learn about the many generative AI software tools that you can use in production, see our guide: Top Generative AI Applications and Tools
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