The Short Answer
If you just want a recommendation: Cursor if you want the most powerful AI-integrated editor right now, GitHub Copilot if you’re already deep in the GitHub ecosystem and want solid completions without switching editors, and Cody if you work with massive enterprise codebases where context matters more than anything else.
But the real answer depends on how you code, what you build, and how much you’re willing to pay. I spent four weeks going back and forth between all three on real projects. Here’s what I found.
What Each Tool Actually Does
All three are AI coding assistants, but they take very different approaches to the same problem.
GitHub Copilot started as an autocomplete tool and grew from there. It lives inside VS Code (and other editors) as an extension. You type, it suggests. Since 2025, it’s added chat, multi-file editing, and agent capabilities – but autocomplete is still its bread and butter.
Cursor is a full IDE built from scratch around AI. It’s a fork of VS Code, so the interface feels familiar, but everything about it is designed for AI-first workflows. Tab completions, inline editing, multi-file agents, background tasks – it’s all native.
Cody by Sourcegraph takes a different angle entirely. Its selling point is deep codebase understanding. Sourcegraph has been indexing and searching code for years, and Cody uses that infrastructure to give the AI much better context about your entire project. One more thing: Sourcegraph recently launched Amp as Cody’s successor for agentic workflows, though Cody still works as the in-editor assistant.
Code Completions: Day-to-Day Experience
This is where you’ll feel the biggest difference in daily work.
Copilot’s completions are fast and reliable. They’ve had years to tune the latency, and it shows. Most suggestions appear in under 200ms. The quality is consistently good – not always perfect, but rarely completely wrong. It handles boilerplate especially well. Writing a React component? It’ll nail the props interface and basic structure almost every time.
Cursor’s Tab completion is something else. It doesn’t just complete the current line – it predicts your next edit across multiple lines, sometimes across multiple files. I was refactoring a TypeScript interface once, and Cursor suggested the corresponding changes in three different files that used that interface. That kind of thing saves serious time.
Cody’s completions are solid but not as polished as the other two. Where Cody shines is when you’re working in a huge monorepo. It pulls in relevant code from across your codebase to inform suggestions, which means the completions are more contextually accurate even if they’re slightly slower to appear.
| Feature | GitHub Copilot | Cursor | Cody |
|---|---|---|---|
| Completion Speed | ~150-200ms | ~200-300ms | ~300-500ms |
| Multi-line Predictions | Yes | Yes (multi-file) | Yes |
| Context Window | Good | Very Good | Excellent (full repo) |
| Accuracy on Boilerplate | Excellent | Excellent | Good |
| Accuracy on Complex Logic | Good | Very Good | Good |
Chat and Inline Editing
All three have chat interfaces where you can ask questions about your code, request changes, or debug issues. The quality varies more than you’d expect.
Copilot Chat works well inside VS Code. You can reference files with @workspace, ask about errors, and request inline edits. The integration is clean. One thing I like: it can access your terminal output and GitHub issues directly. If you’re debugging a CI failure, you can paste the error and it’ll often identify the problem quickly.
Cursor’s chat is tightly integrated with its editor in ways Copilot can’t match. You can select code, hit Cmd+K, and get inline edits applied directly. The “Apply” button diffs your file and merges changes intelligently. Cursor also lets you @mention files, docs, and even web URLs in chat. The Composer feature lets you describe changes across your whole project, and it generates a plan with edits across multiple files.
Cody’s chat leans heavily on its codebase search. Ask it “where is authentication handled?” and it’ll find the actual files in your project, not guess. For large codebases with hundreds of services, this is genuinely useful. The editing capabilities are more basic compared to Cursor, though.
Agent Mode and Autonomous Coding
This is the hot feature of 2026, and all three handle it differently.
Copilot’s agent mode (called “Copilot Coding Agent”) can work on GitHub issues autonomously. You assign an issue to Copilot, it creates a branch, makes changes, runs tests, and opens a PR. I tested it on five medium-complexity issues. It fully solved two, partially solved two more, and completely missed the mark on one. Not bad for autonomous work, honestly. The catch: it only works within GitHub’s ecosystem.
Cursor launched Background Agents in late February 2026. You describe a task, and Cursor spins up a cloud environment to work on it while you keep coding. You can have multiple agents running simultaneously. In my testing, the agent mode handled refactoring tasks well but struggled with anything requiring deep domain knowledge. The iteration speed is fast though – you review, give feedback, and it adjusts.
Sourcegraph’s answer here is Amp, their new agentic coding tool. It’s separate from Cody but uses the same codebase understanding. Amp can execute multi-step tasks, run commands, and iterate on feedback. Early reviews from enterprise teams have been positive, particularly for tasks that span many files.
Model Selection
Which AI models power these tools matters more than most people realize.
Copilot gives you access to GPT-4o, Claude 3.7 Sonnet, and Gemini 2.5 Pro. The free tier limits you to GPT-4o Mini mostly. Pro users get 300 premium model requests per month, which sounds like a lot until you burn through them in a couple of focused days.
Cursor defaults to their own fine-tuned model for fast completions, but you can use Claude Opus 4, GPT-4o, Gemini 2.5 Pro, and others for chat and agent tasks. The Pro plan includes a budget that covers typical usage. If you’re a heavy user, you’ll probably want Pro+ at $60/month to avoid hitting limits.
Cody supports Claude, GPT-4o, Gemini, and Mixtral. Enterprise customers can bring their own API keys or use models through their existing cloud providers. The model selection is flexible, but the free tier is more limited than Copilot’s.
Pricing Breakdown
| Plan | GitHub Copilot | Cursor | Cody |
|---|---|---|---|
| Free | Yes (limited) | Yes (2 weeks trial + limited) | Yes (limited) |
| Individual | $10/mo (Pro) | $20/mo (Pro) | $9/mo (Pro) |
| Power User | $39/mo (Pro+) | $60/mo (Pro+) | N/A |
| Team | $19/user/mo | $40/user/mo | Custom |
| Enterprise | $39/user/mo | Custom | Custom |
Copilot is the cheapest option and has the most generous free tier – you get 2,000 completions and 50 chat messages per month for free. That’s enough for light use.
Cursor costs twice as much at the base level but includes more premium model usage. If you’re coding 6+ hours a day and rely heavily on AI, the $20/month pays for itself in the first week.
Cody Pro is the cheapest paid option at $9/month, but the enterprise pricing (which is where Sourcegraph makes most of its money) can get expensive. For individual developers, Cody’s free tier is decent for trying it out.
Editor Lock-in
Here’s something people don’t talk about enough.
Copilot works in VS Code, JetBrains IDEs, Neovim, and Visual Studio. If you switch editors, Copilot follows you. This flexibility is a real advantage.
Cursor is the editor. You can’t use Cursor’s features in JetBrains or regular VS Code. If you’re a JetBrains user (IntelliJ, PyCharm, WebStorm), Cursor means giving up your preferred IDE. For VS Code users, the switch is painless since Cursor imports all your extensions and settings.
Cody has extensions for VS Code and JetBrains, similar to Copilot. No editor lock-in.
Performance on Real Tasks
I ran each tool through five common development tasks on a mid-size TypeScript/React project (~50k lines). Completely unscientific, but practical.
Task 1: Add a new API endpoint with validation
Copilot handled this cleanly with guided inline completions. Cursor’s Composer generated the entire endpoint, route, validation schema, and tests in one shot. Cody needed more manual guidance but got the validation logic right because it referenced existing patterns in the codebase.
Task 2: Refactor a class into smaller modules
Cursor won this easily. Its multi-file editing made the refactor almost automatic. Copilot required more back-and-forth. Cody identified all the files that needed changes (thanks to its code graph) but the actual edits needed more manual work.
Task 3: Debug a race condition
All three struggled here, which is expected. Copilot’s terminal integration helped it read the error logs. Cursor’s agent mode tried several fixes before landing on the right one. Cody found the relevant async code quickly but its fix suggestion was incomplete.
Task 4: Write unit tests for an existing module
Pretty even across all three. Cursor generated slightly more thorough tests. Copilot’s test suggestions were well-structured. Cody’s tests matched existing test patterns in the project better.
Task 5: Migrate from one library to another
Cursor’s Composer handled this best, generating a migration plan and executing changes across files. Copilot needed file-by-file guidance. Cody’s codebase search found every usage of the old library instantly, which was helpful for planning the migration even if the execution was more manual.
Who Should Use What
Pick GitHub Copilot if:
- You use JetBrains IDEs or switch between editors
- You want the cheapest reliable option
- You’re already paying for GitHub and want everything integrated
- Your team is on GitHub Enterprise and wants managed AI
- You prefer AI as a helper, not a driver
Pick Cursor if:
- You’re a VS Code user willing to switch to a fork
- You want the most advanced AI coding experience available
- Multi-file editing and agent mode matter to you
- You code for 4+ hours daily and want maximum productivity gains
- You don’t mind paying $20-60/month for a serious tool
Pick Cody if:
- You work on large enterprise codebases (100k+ lines)
- Codebase-wide context is more important than fancy editing
- Your company already uses Sourcegraph for code search
- You want the cheapest paid plan ($9/month)
FAQ
Can I use Copilot and Cursor together?
Technically no, since Cursor is its own editor. Some people keep both – VS Code with Copilot for quick edits and Cursor for heavy AI-assisted work. It’s redundant but not uncommon.
Is Cursor just VS Code with AI?
It started that way but has diverged significantly. The AI features are built into the editor core, not bolted on as extensions. The Tab completion, Composer, and agent mode don’t have equivalents in regular VS Code.
What happened to Cody? Is it being replaced by Amp?
Cody still works as an in-editor AI assistant. Amp is Sourcegraph’s new agentic coding tool designed for more autonomous, multi-step tasks. Think of Cody as the assistant and Amp as the agent. Sourcegraph hasn’t announced any plans to sunset Cody.
Which has the best free tier?
GitHub Copilot. The free plan includes 2,000 completions and 50 chat messages per month. Cursor’s free trial is time-limited (2 weeks of pro features, then very limited). Cody Free gives you limited completions and chat.
Do any of these work offline?
No. All three require an internet connection since the AI models run in the cloud. Some completions may be cached locally for speed, but you can’t use any of these tools fully offline.
Which is best for beginners?
Copilot. It’s the least disruptive – install the extension, keep using your editor, and let it suggest code. Cursor can be overwhelming with all its features. Cody is straightforward but its strengths (codebase context) don’t matter much when you’re learning.
Bottom Line
The AI coding assistant space moved fast in 2025-2026. A year ago, Copilot was the only serious option. Now you have genuine competition, and each tool has carved out its niche.
For most individual developers who use VS Code, Cursor at $20/month offers the best overall experience. The multi-file editing and agent capabilities save real time on real projects.
For teams and developers who value editor flexibility, Copilot at $10/month is hard to beat on value. It works everywhere, it’s reliable, and the free tier is generous enough to try before committing.
For enterprise developers drowning in massive codebases, Cody (and increasingly Amp) solves a problem the other two don’t even attempt. If your biggest pain point is “the AI doesn’t understand our codebase,” Sourcegraph’s approach is worth evaluating.
Whichever you pick, you’ll be writing code faster than you were six months ago. The gap between these tools is smaller than the gap between using one and using none.
Looking for more AI development tools? Check out our Best AI Code Editors and IDEs roundup, our hands-on Cursor AI Review, or see how Cursor compares to Windsurf and Claude Code. If you’re interested in fully autonomous coding, we also ranked the 7 Best AI Coding Agents.