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Cursor or GitHub Copilot: Which is the Better AI Coding Tool?

We’re all looking for ways to become better, more productive developers, and the headlines over the last few years suggest that AI coding tools are the way to go. Two of the most well-known tools are GitHub Copilot, which suggests code much like autocomplete in Gmail, and Cursor, an IDE extension built on Microsoft VSC that has taken the internet by storm after their influencer campaign featured 8-year-olds building websites.

But developers are left with many questions, which we’ll look at in this article.

Table of Contents

GitHub Copilot or Cursor AI? Comparing AI Dev Tools

Is GitHub Copilot Worth the Money?

GitHub Copilot is primarily an extension for your IDE. First of all, this means you’re still working in the same place you’ve always worked. The advantage of this is it’s familiar, but it’s still restrictive—Copilot doesn’t allow you to give the AI tasks while you’re away from your desk and come back to the results. No interacting with the AI from your mobile or setting multiple tasks to run while you’re in meetings or working on other features.

However, the interaction means that you should have a fairly good understanding of what Copilot is doing. As it only adds a few lines of code at a time, it’s very easy to stay on top of the suggestions made by the AI and fix issues.

According to GitHub, predictive text (the main feature of Copilot) allows developers to reach task completion 55% faster. Presumably, they’re referring to the task of writing the code, not including planning, testing, and problem-solving.

However, in other surveys, developers reported deleting more generated code than they keep, struggling with hallucinations, and concerns about copyright.

GitHub Copilot draws on the open tabs in your IDE as its knowledge source to complete your tasks, which is one reason why its usefulness is limited; it doesn’t know what’s happening in the rest of your codebase. It’s like bringing on a freelancer to do one task, but not explaining how your software works, not allowing them to see the codebase, and not explaining your own style rules. They can take a pretty good attempt at the task in theory, but in practice, it’s unlikely to be what you’re looking for. Other AI developer tools solve this problem by adding more context—we’ll look into this later. The only way to get fully context-aware answers in GitHub Copilot is to sign up for their enterprise plan, which is only available for existing GitHub enterprise customers.

Similarly, many other GitHub Copilot features are restricted to enterprise users, including PR summaries, knowledge bases, and web-based chat. Other tools aimed at small teams and individual developers, such as Fine, offer all these features in regular plans.

GitHub Copilot offers an individual plan at $10 per user, but the functionalities are so limited that to get the most out of it, the business plan at $19 per user is more relevant. This comes in more expensive than alternatives and, as mentioned, still doesn’t offer all the features. You get unlimited messages and interactions, including code completion.

So in summary, while it’s worth trying out Copilot if you have the money for extra tools, this isn’t the AI coding revolution that you’ve been promised, and it’s worth checking out alternatives. It’s certainly better than writing all your code from scratch.

Is Cursor Worth the Money?

Many people “graduated” from GitHub Copilot to Cursor, with Cursor considered to be a more effective tool for AI code generation. Cursor claims to go beyond simple code completion by offering in-line explanations, documentation, and contextual search, which can be valuable for complex projects. Cursor can be used to create boilerplate code for entire features and programs, offering a far larger scope of work.

Some people complain that Cursor, as a fork of VSCode and not a plugin, has drawbacks such as not being able to debug within the same IDE and needing to copy-paste code between platforms.

Cursor supports most coding languages (of course, the more common the language, the better the results) and provides real-time code suggestions and instant feedback. Working with Cursor is like sitting down with another smart programmer and sharing notes, working together on a project.

Cursor is great with natural language commands, hence the low barrier to entry demonstrated by many users on social media. Even people with little-to-no coding knowledge can get started by writing commands in plain English, just like in ChatGPT, and getting a code output. For more advanced developers and companies building commercial products, this is definitely a nice-to-have, but the benefits trail off quickly as in-depth knowledge and understanding of the code is required to know what to ask of the AI in order to improve the software.

Cursor offers a limited free plan that also includes a 2-week free trial of pro features, usually worth $20 per month. All the plans are usage-based, and while the Pro plan includes unlimited completions (of code), Cursor limits which LLM you can use and after a while, limits you to “slow premium” uses.

For beginners looking to build hobby projects, or non-tech startup founders who want to validate an idea, Cursor can be a great entry tool to build out an MVP. You’ll need some level of understanding, but that’s nothing you can’t learn with a few YouTube videos. For more experienced developers, Cursor is a useful addition to the tech stack and at $20 a month is hardly going to break the bank, so we’ll rate it as worth the money—but it’s not going to change your life.

What Are the Main Differences Between GitHub Copilot and Cursor?

  • GitHub Copilot solely uses OpenAI’s GPT, while Cursor supports GPT and Claude models.
  • Pricing-wise they’re similar, as for the functionalities most developers look for, you’ll need the $20 plan. If you’re an enterprise customer of GitHub, however, GitHub Enterprise seems to be worth the extra investment (although the same features are available from Fine at a fraction of the cost).
  • Cursor integrates additional features like in-line documentation and contextual search directly into the IDE, while GitHub Copilot primarily integrates as a code suggestion tool without these extras.
  • Cursor's added features can sometimes slow down the workflow for developers seeking quick solutions, whereas GitHub Copilot's simpler interface is more straightforward but offers fewer advanced features.

Why Do GitHub Copilot and Cursor Hallucinate Code?

GitHub Copilot and Cursor hallucinate code primarily because they operate with limited context and can't fully interact with the entire codebase. These AI tools generate code based on patterns from their training data, but they don’t have a complete understanding of the specific project they’re working on. Since they can't access or comprehend the entire codebase, they often make suggestions that are out of context, incorrect, or irrelevant. For developers, this severely limits the usefulness of both tools, as it requires them to spend extra time reviewing, correcting, or discarding the AI-generated code, ultimately reducing the efficiency these tools are supposed to provide.

The more context a tool has, the more accurate the code output will be. That’s why GitHub Copilot Enterprise is much more successful than the regular plan and why many people opt for platforms such as Fine, which offer the same features at a more accessible price for all developers.

Similarly, AI can be used to test and find its own hallucinations by running the code and seeing if the desired result is achieved. Although this isn’t offered by GitHub Copilot and Cursor, other AI Coding tools such as Fine make it easy to do.

How to Prevent Hallucinations in AI Coding?

To prevent hallucinations in AI coding, give your AI as much context from your codebase as possible. If you’re using ChatGPT, this means copying and pasting the code so it knows to what to refer. Tools like Fine integrate with your tech stack and build a knowledge graph for the AI so that you won’t need to copy-and-paste, saving time. In addition, set your AI to automatically analyze and test new PRs, so that if it fails, it can fix and improve the code.

Do I Need Cursor If I Already Pay for Copilot?

Although there are some differences between what the platforms offer, there doesn’t seem to be enough variation (at the moment) to justify spending on both tools, given that their primary focus is code generation. While some developers are canceling their Copilot subscriptions in favor of Cursor, this seems to be based on the trends seen on social media. Many others are subscribed to one platform only and aren’t using it much because of their limitations, and would benefit from a different platform entirely that offers more than code generation.

What Other AI Coding Tools Are There?

Fine (Available to all)

Fine is the end-to-end AI coding solution that integrates with your tech stack and helps with tasks from every step of the development lifecycle. It offers automations called Workflows, so AI processes can kick into place automatically, and is based on a unique knowledge graph called Atlas, which increases output accuracy. Fine isn’t just for generating code, it’s for a smoother development process. Plus, it’s cloud-based and mobile-friendly, so there’s no reason you can’t code from anywhere.

Devin (Available on request and approval)

Devin took the dev world by storm thanks to their successful marketing campaign in March. They promise a full AI development assistant, which can plan, execute, and debug on its own. It’s familiar with many programming languages and aware of technical jargon. However, the platform isn’t publicly available. You have to request access via their website.

Magic (Unavailable)

Magic recently raised $320m in another fundraising round and their mission is to join the likes of Fine, Cursor, and GitHub Copilot in offering software to help developers with generating code, AI workflows, and even AGI that can solve problems better than humans can. Unlike the others, instead of relying on the existing LLMs, they’re developing what they call “Long-Term Memory” to shift the focus from training to context. Magic isn’t yet available to the public, but they’ve made it clear they’re focusing on applying their technologies specifically to the software development industry.

Try Fine - Free 7 Day Trial

Fine offers many of the features that GitHub Copilot offers on the enterprise plan, and more. It’s designed to help developers with their work across the dev lifecycle, solving many of the issues with Copilot and Cursor. Try it now, free for 7 days.

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