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GitHub Copilot vs ChatGPT vs Tabnine: A Comprehensive Feature Comparison with Pieces

GitHub Copilot vs ChatGPT vs Tabnine: A Comprehensive Feature Comparison with Pieces
A comparison of GitHub Copilot, ChatGPT, and TabNine.

As a software developer, you're always looking for ways to work more efficiently. So when it comes to which tools to use, the best answer is often, “Use multiple tools!” A few of the most popular and useful AI workflow tools in the news today are GitHub’s Copilot, Tabnine, ChatGPT, and Pieces for Developers, which was recently showcased on a GitHub live stream and in the TLDR newsletter.

In this article, we’ll give a full breakdown of GitHub Copilot vs ChatGPT vs Tabnine: What these tools do, how their generative AI capabilities can make you a better developer, and how Pieces for Developers functions as the AI-Teammate to the code generation tools used by millions of developers around the world.

Using Pieces with ChatGPT.

So… GitHub Copilot vs ChatGPT vs Tabnine? Let’s Discuss

GitHub Copilot is an AI-powered code completion tool that uses machine learning models to suggest code snippets and complete code as you write in your editor. It harnesses the power of OpenAI Codex, a generative pre-trained language model, and can save you time and effort by eliminating the need for you to write every line of code from scratch.

Tabnine is another AI-powered code auto-completion tool that predicts the most likely code snippet based on the context of what you're typing. It's highly customizable, can be used with a variety of programming languages, and includes features such as code formatting, documentation, and language detection.

ChatGPT is the fastest-growing web app of all time. Tens of millions of people use it to help answer all kinds of questions. From writing emails to drafting trip itineraries, ChatGPT can help answer questions and take on the persona of an “expert” in any given profession. Naturally, developers have started using the tool to help generate code, debug, and find solutions to complex problems.

Finally, Pieces for Developers is an advanced code snippet manager and workflow helper designed to optimize developer workflows and eliminate the chaos of context switching. It allows you to quickly save, enrich, search, transform, and share code snippets throughout your workflow, making it a great companion for developers who use all kinds of tools and need an AI Teammate to curate their code snippets, both written and generated.

As AI-generated materials become more ubiquitous and created by many more people with varying degrees of technical proficiency, the need to store and understand these materials becomes ever more apparent. This is where tools like Pieces for Developers come in. Pieces can be used to help solve the curation and contextualization issues that arise with massive amounts of data and new information.

Let’s take a closer look at using Pieces with GitHub Copilot vs ChatGPT vs Tabnine: how they work, the cost of each, and how you can use them together to improve your productivity and efficiency as a software developer.

A Brief History of the Development of These Tools

GitHub Copilot

GitHub’s Copilot is an AI-powered code completion tool created by OpenAI and GitHub. The tool was announced in June 2021 and was made publicly available in a limited technical preview the same month.

The development of Copilot began in 2020 as a collaboration between OpenAI and GitHub. OpenAI's GPT-3 language model, which was trained on a massive dataset of text and code from the internet, was used to generate code snippets based on natural language input.

GitHub Copilot is built on top of OpenAI's Codex, which is a neural network trained on a massive dataset of code. Codex can generate code for a wide range of programming languages and can even write entire functions based on natural language descriptions. Copilot uses Codex to provide suggestions and autocompletions for code as developers write.

GitHub and OpenAI have emphasized that Copilot is intended to be a tool to help developers write better code, not to replace developers altogether. They have also stated that Copilot has been trained on a dataset of open-source code and that the tool is designed to encourage good coding practices, such as properly attributing code sources.

Copilot and Copilot for Business are now paid plans from GitHub and are set to become one of the company’s primary sources of revenue. The “Copilot” brand, referring to the OpenAI Codex, has now been deployed across the M365 suite of tools, a sign that Microsoft is committed to the integration of AI as a core business strategy.


Tabnine is an AI-powered code completion tool that is managed and developed by an Israeli company called Codota. Codota was founded in 2015 by Dror Weiss and Eran Yahav, who are both experts in the fields of machine learning and artificial intelligence.

Since the early days of Codota, the company was focused on developing a platform that could provide code recommendations to software developers. The goal was to make it easier and faster for developers to write code by providing them with suggestions based on the context of the code they’re writing.

In 2019, Codota acquired Tabnine, an AI-powered code completion tool that uses deep learning algorithms to provide highly accurate code suggestions to developers. Tabnine was subsequently rolled out by Codota and adopted for use by individual developers and large tech companies alike, who utilize the tool for its speedy and accurate code completions.


ChatGPT is a large language model developed by OpenAI on the GPT-3 architecture. GPT-3 is a state-of-the-art natural language processing model that can generate human-like language and code, answer questions, and perform a wide range of other language-related tasks.

OpenAI began working on GPT-3 in 2019, and it was publicly released in June 2020. Since then, the model has been continuously updated and improved. They released the latest version, GPT-4, in March 2023.

ChatGPT is one of the many applications of the GPT-3/3.5/4 model. It allows users to interact with the model in a conversational manner, asking it questions or giving it prompts to generate responses. ChatGPT can be accessed through various platforms, including OpenAI's API, which allows developers to integrate the model into their applications.

The development of ChatGPT is part of a broader trend in natural language processing towards more sophisticated language models that can handle more complex tasks. As these models become more advanced, they have the potential to revolutionize the way we interact with technology by making it more intuitive and human-like.

Despite the success of ChatGPT and the LLMs, the trend is now starting to shift towards smaller models that are designed for more specific tasks. This was addressed by Sam Altman, the CEO of OpenAI, where he emphasized that the importance should not be put on the size of the model, but on the performance and capabilities.

Pieces for Developers

Pieces was founded in 2021 with the goal to make the atomic components of a creator’s workflow easier to save, enrich, search, transform, and share. Their flagship tool is Pieces for Developers, a desktop application that pairs with integrations and extensions throughout a developer’s existing tools, like browser extensions for research and IDE plugins for code completion, organization, and more.

Pieces for Developers is the most advanced snippet management tool on the market. It’s powered by a combination of AI from in-house models and OpenAI’s APIs. While it’s an excellent companion to existing tools, it can also be used as a free Tabnine or Copilot alternative to accelerate your development workflow.

The team at Pieces is constantly releasing new features across the suite of tools, all with the intent to make a user’s experience as seamless as possible.

Generative AI’s Capabilities

Generative AI refers to a type of artificial intelligence that can create new content or generate output that is similar to what a human might create. This is in contrast to other types of AI, such as discriminative models, which are designed to classify or categorize input data.

Generative AI models use techniques such as deep learning, neural networks, and probabilistic modeling to analyze patterns in data and generate new content. For example, a generative model might analyze a dataset of code snippets and then be able to create new, useful code completions based on what it learned from the dataset. This is how the generative AI capabilities of the tools in this article can “write” code for you.

GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor. On the other hand, Tabnine uses an in-house, code specific LLM to facilitate code auto-completion. These models are trained on open-source code with permissive licenses (MIT, Apache 2.0, BSD-2-Clause, BSD-3-Clause) and your personal repos.

Similar to Tabnine, the on-device AI capabilities of Pieces for Developers are powered by fine-tuned small language models, while the online version works in conjunction with the latest from OpenAI and Gemini. Pieces also has the ability to run completely offline and on-device using the offline AI tools that power the offline enrichment and context generation that make snippets more usable. This gives snippet savers the ability to access those snippets in a secure environment that avoids public LLMs and the data security issues that come along with them. See what the best LLM for coding is based on our recent post.

While Copilot vs Tabnine are both using AI mostly, if not entirely, for the task of code completion, Pieces approaches the productivity and efficiency formula differently. The core user of Pieces is someone who wants to save their snippets and gather information about them. They are developers who are working on multiple projects, want to stay organized, and are pioneering creative solutions to the problems they are working on.

Once you save or paste materials to Pieces, you can auto-complete code based on saved snippets from your Pieces micro-repo. As you continue to save, Pieces will learn from your saved snippets and auto-save for you. This ability to save AI-generated snippets and quickly gather context was a major highlight from the recent GitHub interview. The context that the AI captures includes auto-generated descriptions, tags, language classification, relevant people, related links and more - powering the intuitive Global Search feature that makes it easy to find and reuse materials as you need them.

Discover the 9 best AI code generation tools for developers.

A feature comparison chart of GitHub Copilot vs ChatGPT vs Tabnine.

How the AI in each software learns and improves over time

Natural language to code is the baseline for all of these tools. GitHub Copilot suggests code as you go. This means that the AI pair programmer evaluates the context of the code in your IDE and suggests code and entire functions in real time. Tabnine learns from your personal repo and offers an autocomplete capability that will suggest your next lines of code based on context and syntax.

Pieces for Developers will autocomplete from your Pieces desktop app. You can think of the desktop app as an AI-powered micro-repo for your code. This gets your code out of a notes app or Google Doc and into a searchable, AI-enriched snippet manager.

Similar to Tabnine’s ability to autocomplete from your repo, Pieces has a feature called Snippet Discovery. This allows a user to drag and drop an entire repository into Pieces and watch as the AI identifies snippets that are common or repeated throughout. These snippets will be automatically enriched and then suggested as autocompletions as you code. You can then transform that code to be readable, into boilerplate, to be more performant, or to convert the code to another language altogether, without leaving the Pieces desktop app.

Just as Copilot is integrated with the Microsoft 365 suite, Pieces’ Snippet Discovery unearths snippets from websites you browse and from the technical conversations you have in Microsoft Teams.


GitHub Copilot

GitHub Copilot is compatible with various integrated development environments (IDEs), including Visual Studio Code and JetBrains IDEs.

If you’re using VS Code, installing GitHub Copilot will allow you to autocomplete code as you type. You can enable or disable GitHub Copilot after installation and customize advanced settings within VS Code or on GitHub.com. Similarly, if you use a JetBrains IDE, GitHub Copilot can autocomplete code as you type. However, configuring advanced settings may differ depending on the JetBrains IDE you use.

You can also configure advanced settings for GitHub Copilot. For example, you can set the maximum number of suggestions that GitHub Copilot should provide, or you can enable or disable certain types of suggestions.


Tabnine supports a wide range of IDEs, including Visual Studio and JetBrains IDEs, making it accessible to well over 40 million developers.

Once installed as a plugin in an IDE, Tabnine utilizes their code-specific ML to provide intelligent code autocompletion. It analyzes the context of the code being written, the programming language in use, and the project being developed to suggest accurate and relevant code completions. Tabnine is capable of providing autocompletion for over 25 programming languages, including popular languages like Java, Python, JavaScript, and C++. Tabnine also offers a range of customization options to suit individual developer preferences.

Pieces for Developers

Pieces can be easily installed from various marketplaces as an IDE extension for popular tools like VS Code and JetBrains’ IntelliJ, as well as Chrome, Firefox, Brave, Opera, and Edge browsers. The desktop app provides users with the ability to share GitHub gists with AI-generated context, discover snippets from their GitHub repositories, and more.

As a desktop application, Pieces serves as a home base for the modern developer workflow, allowing for AI-powered snippet management, autocomplete, enrichment, and sharing functionality across all tools.

One of the key benefits of using Pieces is the ability to work as a tool-between-tools, making it an excellent AI teammate to other generative AI tools like Copilot, TabNine, and ChatGPT.

The upcoming Microsoft Teams integration will provide developers with even more capabilities. They will be able to discover snippets from conversations and capture the context of those conversations and the people involved to relate to the specific snippet or collection of snippets. This functionality will help developers to improve collaboration, onboard new teammates, and share knowledge, thereby streamlining their workflows and saving time.


A price comparison chart of the four tools discussed in this article.


GitHub Copilot vs ChatGPT vs Tabnine makes for an interesting comparison. Each is a powerful AI copilot that can improve developer productivity. While each one has its merits, combining multiple tools will continue to be the best solution to help developers work smarter. As the amount of generated material continues to grow at an exponential rate, the need for a place to save those materials becomes greater every day.

Whether browsing Stack Overflow, generating code in ChatGPT, or discussing a problem with your team, you can curate your snippets with Pieces for Developers. Once you save your first snippet, explore the powerful features of the desktop app, plugins, and extensions. Soon, you won’t be able to remember how you curated code in a world of generation without Pieces.

Want to explore all of Pieces’ cutting-edge features? View our documentation.

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