A very subjective comparison of Claude Code, OpenCode, Cursor & GitHub Copilot

MMaximilian Schwarzmüller
컴퓨터/소프트웨어자격증/평생교육AI/미래기술

Transcript

00:00:00There is a broad variety of tools you can use for agentic engineering, so for working on code with
00:00:06help of AI. And amongst the most popular these days of course are Cloud Code, Open Code, Cursor,
00:00:13and Visual Studio Code with GitHub Copilot. Of course there also is Google Anti-Gravity,
00:00:18there is Codex, Gemini CLI, and you know what? These are the tools I've used a lot over the
00:00:24last couple of months though simply because I continuously want to test what's available
00:00:29and how well these tools work. I've built actual projects like buildmygraphic.com and more projects
00:00:35which are about to be released soon and many internal projects. And I've built entire courses
00:00:41like this one here which I recently updated where I dive into Cursor and GitHub Copilot or this one
00:00:46here which I released yesterday where I dive into Cloud Code. But in this video I want to give you
00:00:53an overview of these tools, their different capabilities and my opinion on them. And the
00:00:59first important difference of course is that we can kind of divide them into two camps if you will.
00:01:05Because we have the CLIs or TUIs, the terminal user interfaces or command line interfaces
00:01:12and we got those IDEs here. Now to be fair Open Code actually has a web mode too so you can start
00:01:23a local server on your system and then use a web user interface for working with Open Code. But the
00:01:31default mode in which I've only used it is the TUI mode which is then the same kind of mode you have
00:01:37with Cloud Code. So where you run Open Code after installing it in one of your projects and you then
00:01:44interact with it from inside your command line, inside your terminal. Just as it's the case with
00:01:49Cloud Code by default. It's worth pointing out that both Open Code and also Cloud Code have IDE
00:01:57integrations so they can integrate with those IDEs and for example show code changes or previews of
00:02:04the intended code changes in the IDE or allow you to interact with them in an IDE. Those integrations
00:02:12exist but I think it's fair to say that they're really optimized and primarily built to be used
00:02:19from the command line, from the terminal therefore. So that's what I mean when I say they are CLIs or
00:02:25TUIs, terminal user interfaces. One important reason for why Cloud Code and Open Code are primarily
00:02:32built for the terminal or to be used as an extension in existing IDEs instead of being VS code forks like
00:02:40Cursor or Windsor for example are is of course that for the developers this gives them more flexibility
00:02:49you could say. They don't need to worry about all the features an IDE needs to have instead they can
00:02:55focus on building good agents, good tools that can help you generate and edit code with AI. Now of
00:03:04course one downside if you want to call it like this is that of course these IDEs therefore offer
00:03:10a bit more than just AI agents, just chat interfaces for you to interact with. Cursor for example has
00:03:18amazing auto-completion where you can really fly through your code base by hitting TAB TAB TAB and
00:03:26applying edits in an entire file and even across files and I would say GitHub Copilot has decent
00:03:34auto-completion. It's definitely worse than cursors in my opinion but it's also good and most
00:03:39importantly it's there because of course with these CLIs with Cloud Code and Open Code there is no
00:03:46auto-completion in your editor at least not powered by these tools. They are instead agents or agentic
00:03:55tools which means that you interact with a chat that triggers AI you could say. So that is what
00:04:02these tools are and of course Cursor and VS Code with GitHub Copilot also offer that in addition to
00:04:08the auto-completion. You have that sidebar here in VS Code where you can interact with GitHub Copilot
00:04:14and you have the same in Cursor of course but with Open Code and Cloud Code that is your primary and
00:04:21only way of interacting in the end. Now of course since they are AI agents in the end or since they
00:04:28are about agentic engineering one of the questions that matters the most is which AI models are
00:04:34supported by these different tools. And here for Cloud Code that is essentially anthropics models
00:04:42so talking Haiku, Sonnet and of course Opus there and because Cloud Code is by the same company
00:04:51as these models, Anthropic, the integration is of course pretty good and these models in my
00:04:57experience tend to work really well in Cloud Code. And I'm saying that because of course these
00:05:02same models are also available in these other tools when using GitHub Copilot I can of course select
00:05:10those Anthropic models as well but they run in a different harness here. They run in the GitHub
00:05:17Copilot or the Cursor harness or the Open Code harness and all these harnesses are also good
00:05:23but especially that combination of Cloud Code with those anthropic models is really good in my
00:05:29experience. It is worth mentioning though that very recently there also has been an announcement
00:05:35that Cloud Code also integrates with Ollama and in case you don't know Ollama is a tool that can be
00:05:41used to run open AI models on your system if your system is capable enough for that of course. So you
00:05:49can in theory use Cloud Code with open models which kind of makes it free because they're running on
00:05:54your system you're only paying for your electricity there of course. The downside is that these models
00:06:01at least right now are typically not as capable as the anthropic models especially like Opus for
00:06:08example and even if they are or were we would be talking about models that need lots of GPU RAM,
00:06:16lots of video RAM and quite capable hardware resources in general to put it like this so they
00:06:22would not run on your laptop or your Mac Mini or whatever it is. So that's worth noting but the
00:06:29support is there and of course depending on your system and the development of future open models
00:06:35that might be a viable option. So we also have that Ollama support here. Now you can also use
00:06:42Ollama with OpenCode and Cursor and VS Code and all those other tools also support lots of other
00:06:51models. I mean in OpenCode if you just type models you'll find a very long list of models to choose
00:06:59from from different providers and most importantly also from different subscriptions you may have.
00:07:05Now there has been a time where you could use OpenCode with your Cloud Code Max subscription
00:07:12for example and you could use those anthropic models in OpenCode through that subscription
00:07:17which was pretty nice because I personally actually preferred the UI and in many parts also the
00:07:24behavior of OpenCode over Cloud Code. I think OpenCode is a really amazing piece of software,
00:07:30it's also open source by the way, I'll get back to that, but anthropic cracked down on that and you
00:07:36can no longer use your Cloud Code Max subscription in OpenCode. You can for example use your GitHub
00:07:43Copilot subscription though. So you can use that subscription here with OpenCode of course also
00:07:50with GitHub Copilot and that of course is pretty nice because then you have that subscription
00:07:54model which you already may be paying for and you can try those models in OpenCode besides using
00:08:00them of course in GitHub Copilot in VS Code for example so that's pretty nice. But no matter which
00:08:06payment model you're using you have access to many many models in all these three tools not so much in
00:08:13Cloud Code though. Now I already just mentioned it OpenCode is open source. It is open source and the
00:08:20advantage of that of course is a very transparent development, a very community driven development,
00:08:25rapid innovation though I will say that's true for all these tools essentially. Maybe GitHub Copilot
00:08:32is lagging a bit but they're also very quick at catching up and implementing all the features other
00:08:38tools may be adding but nonetheless it's pretty nice that OpenCode is an open source alternative
00:08:43community driven nonetheless OpenCode also offers a subscription. There is OpenCode black which offers
00:08:50different tiers just like the anthropic or the GitHub Copilot subscriptions or the cursor
00:08:55subscriptions of course to give you some included usage so that you don't have to pay for the actual
00:09:02usage but instead you have a flat fee and then some included usage so to say. So that's available here
00:09:07as well even though OpenCode is open source. So we have paid subscriptions available for Cloud Code,
00:09:14OpenCode, cursor also has them and also there are subscription plans for GitHub Copilot. Now for
00:09:20Cloud Code you need a paid subscription for OpenCode it is optional and as mentioned you can also use
00:09:26your GitHub Copilot subscription in OpenCode that is an option too. What's worth noting here is that
00:09:31of course OpenCode is pretty much the only tool that needs to be profitable I would guess at least
00:09:39because it's not a big VC funded company or anything like that it's not Microsoft like in the
00:09:46case of GitHub Copilot so they kind of have to find a model where they make money with those
00:09:52subscriptions. Cloud Code, cursor and I guess also GitHub Copilot in the end are all heavily
00:09:58subsidized by their companies because they're either VC funded or Microsoft so you get probably
00:10:05a bit more usage out of your Cloud Code, cursor and GitHub Copilot plans than you may be getting
00:10:11out of OpenCode but that of course also depends on which models you're using and so on and it may not
00:10:17actually be a problem. Now let's talk features. Which features are supported? The short answer is
00:10:22if there's a good feature in one model the others are quick to catch up. Now to me it seems as if
00:10:29Cloud Code has been the the driver of many new features so has to some degree been cursor
00:10:38GitHub Copilot tended to lag behind a bit but if we look at features which are by the way also all
00:10:45cover in my recently released Cloud Code course and also in that AI for developers course I mentioned
00:10:50if we look at features like sub-agents if we look at features like agent skills they are supported
00:10:57by all these tools so you will find respective entries in the documentation of OpenCode and
00:11:04also of all the other providers so they all have these features available. The one thing worth
00:11:12noting maybe is that in case of OpenCode agents is a term that kind of comprises two things you could
00:11:19say it's a combination of different modes in which you can run OpenCode and agents to which work can
00:11:26be outsourced. In Cloud Code's case an agent is really just a sub-agent that's invoked to perform
00:11:34a specific task like explore documentation for example. In OpenCode you have different agents
00:11:42through which you can cycle with the tab key for example to switch between plan mode and edit mode
00:11:47so you have a plan and an added agent in Cloud Code these things are called modes so that's something
00:11:53worth noting but ultimately you'll find all these features like agents and skills in all these tools
00:12:01and if it's missing in one tool you can be sure that it will soon be supported. The same is true
00:12:05for memory or rules files they are also supported in all these tools so that you can set up files
00:12:13in which you set up some general rules that should always be followed or where you share some learnings
00:12:18that should be considered by all chat sessions. Here in Cloud Code it's the Cloud MD file and you
00:12:24can also set up some some rules in a rules directory but in OpenCode that would be the
00:12:31agents MD file and also the Cloud MD file so that supports both. Agents MD is in theory an open
00:12:40standard which is indeed supported by cursor as well so we have agents MD in cursor as well and
00:12:50also in GitHub Copilot. Cursor then also has its own cursor rules and GitHub Copilot has its own
00:12:57GitHub Copilot rules so that's there in addition. Here that would be my Clod rules so those are not
00:13:06compatible and that's kind of the annoying part here as you see in theory agents MD would be
00:13:12compatible and would be shared but Clod Code plays Apple here and doesn't support agents MD instead
00:13:18it has Clod MD but that is supported by OpenCode but not by the other tools as far as I know so
00:13:24yeah that is kind of annoying and in general also when it comes to these agent skills for example
00:13:29they are supported by all the different models but they have to be stored in very different
00:13:34folders so for example when you're using OpenCode you would store your skills in an OpenCode skills
00:13:41folder or in Clod skills it does support that for compatibility. If you're working with Clod it's
00:13:48just the Clod skills folder that is supported. With cursor it's cursor skills or also Clod skills or
00:13:58Codex skills for that compatibility but not OpenCode skills and with Visual Studio Code and GitHub
00:14:05Copilot it is .GitHub skills or also Clod skills. So Clod skills works everywhere but as you can
00:14:13also see we're still in that age where a lot of things are still evolving and every provider tries
00:14:20to have its own configuration its own settings and force that upon others so yeah that will definitely
00:14:28change in the future and I'm sure in a year or two it will all be way more standardized but right now
00:14:34it's lots of different folders and lots of things to look up in the documentation and of course things
00:14:39also change frequently and when this video comes out some things may already be different for example.
00:14:45These tools also all have support for MCP servers so that you can for example install the
00:14:51playwright server to give them browser access they have access to web fetch so they can send
00:14:57web requests so that you can for example tell them to go to some documentation page and read
00:15:02the content from that page so that's of course useful and therefore ultimately from a pure
00:15:08feature perspective from my experience there aren't a lot of differences. Sure, configuration settings
00:15:14may differ some niche feature may exist in one tool but not the other but when it comes to the
00:15:18main features on which there is some consensus that they are good they are typically supported
00:15:24in all the tools and as I mentioned earlier if a good feature is added and is missing in one tool
00:15:28you can be sure that it will be added there soon enough too. But what about the quality of these
00:15:34tools? What's my verdict on these tools? Which one should you use? Which one produces the best results?
00:15:40I'm sorry but ultimately all these tools are decent. Super boring answer I know but what should I do?
00:15:48They are all decent. I've used them all and there is no tool here where I would say that's horrible.
00:15:54As I said initially in my experience Claude code works really well especially when used with Opus
00:16:00because it's the harness by the same company that built the tools you can kind of feel that you get
00:16:07really good results out of Claude code with those anthropic models. I also will say though that there
00:16:13was a period where I felt like GitHub Copilot gave pretty good results with those anthropic models to
00:16:18some degree better but that's also very subjective and may depend on the exact project you're working
00:16:24on. Now what I definitely do like is that with OpenCode and Cursor and GitHub Copilot I can also
00:16:30use other models because for example there is the GPD 5.2 codecs model. I think that's the name.
00:16:39It's an amazing model for coding that's not available in Claude code that is available in
00:16:46these other tools and it's a model I like a lot. I like to use that for example for more complex
00:16:53tasks so that's when I switch over to OpenCode. I have a GitHub Copilot subscription so I can use
00:16:58that through that subscription or with a Cursor subscription you can use it in Cursor so that is
00:17:04when I would switch when I want to use a model that's not available in Claude code or I'll also
00:17:09be honest sometimes or for certain tasks I prefer having an IDE because I know that I'll need to do
00:17:15more edits on my own because I want to have like a nice div view of course Cursor and GitHub Copilot
00:17:22once they're done with their changes give you a nice overview of what changed and you can accept or
00:17:28deny these changes on a change by change basis and there are certain tasks where I like having that
00:17:34so that would be situations where I use these IDEs instead. If we're just talking about the code
00:17:41quality then again as mentioned I can't really say that one tool is worse than the others it's AI and
00:17:49I've had very bad results with all of them I had good results with all of them and the most important
00:17:55part will always be your prompt the context you provide that you use features like agents and
00:18:02skills especially skills can be very useful for providing extra knowledge but that of course then
00:18:08applies to all these tools that is your task as a developer because we're not talking about
00:18:13wipe coding here we're talking about agentic engineering where you leverage your skills
00:18:18as a developer where you try to give the AI information it can work with and where you
00:18:23review the solution the AI came up with and here all these tools can do a good job.

Key Takeaway

While AI coding tools vary between terminal-based agents and full IDEs, they are reaching feature parity, making the developer's ability to provide context and review code more important than the specific tool chosen.

Highlights

Comparison of four major AI engineering tools: Claude Code, OpenCode, Cursor, and GitHub Copilot.

Categorization of tools into Terminal User Interfaces (TUIs/CLIs) versus Integrated Development Environments (IDEs).

Analysis of model support, highlighting Claude Code's optimization for Anthropic's models and OpenCode's open-source flexibility.

Discussion on the lack of standardization for configuration files like agents.md and rules folders across different providers.

Evaluation of feature parity, noting that sub-agents, skills, and memory systems are becoming standard across all platforms.

The speaker's verdict that tool quality is subjective and heavily dependent on the developer's prompting and review process.

Timeline

Introduction to Agentic Engineering Tools

The speaker introduces the landscape of modern agentic engineering tools used for AI-assisted coding. He identifies the primary contenders as Claude Code, OpenCode, Cursor, and GitHub Copilot, while also mentioning secondary options like Codex and Gemini CLI. Over the past few months, the speaker has tested these tools extensively while building real-world projects and educational courses. This section sets the stage for a subjective comparison based on hands-on experience rather than theoretical benchmarks. He emphasizes his goal of providing a clear overview of capabilities and personal opinions to help users choose the right tool.

CLIs vs. IDEs: Understanding the Interface Gap

A major distinction is made between terminal-based interfaces (TUIs/CLIs) and full IDEs like Cursor or VS Code with Copilot. Claude Code and OpenCode primarily operate within the terminal, allowing developers to maintain focus on agentic logic without the overhead of an entire editor. While these terminal tools offer some IDE integration, they lack the seamless 'TAB' auto-completion features found in Cursor. The speaker notes that IDE-based tools offer a more visual experience with sidebars and better file-wide edits. This section explains that choosing between them depends on whether a developer prefers a specialized AI agent or an all-in-one coding environment.

Model Support and Subscription Models

The discussion shifts to the specific AI models each tool supports and how users pay for them. Claude Code is tightly integrated with Anthropic’s models like Sonnet and Opus, which the speaker finds provides a very high-quality experience. OpenCode is highlighted as a unique open-source alternative that allows users to bring their own subscriptions, such as GitHub Copilot, to access various models. Interestingly, the speaker mentions that some companies 'subsidize' their tools via VC funding, whereas OpenCode must remain profitable. He also touches on Ollama support, which allows for running open models locally, potentially making the AI usage free at the cost of hardware resources.

Features, Skills, and Fragmented Standards

The speaker examines common features such as sub-agents, agent skills, and memory rules, which are present in almost all the tools. He points out a frustrating lack of standardization regarding configuration files like 'agents.md' or 'claud.md', noting that companies often 'play Apple' by forcing their own standards. Most tools now support MCP servers for browser access and web fetching to read external documentation. While features are largely at parity, the directory structures for skills vary significantly between platforms. The speaker predicts that these fragmented configuration styles will likely become more standardized over the next year or two.

Final Verdict: Code Quality and Performance

In the concluding section, the speaker gives a 'boring' but honest answer: all the compared tools are decent and capable of producing good results. He admits to preferring Claude Code for its harness optimization but switches to OpenCode or Cursor when he needs specific models like GPT-5.2 Codex. He highlights that AI tools can produce bad results regardless of the brand, emphasizing that the developer's prompt and context are the true variables. Ultimately, the review process and 'agentic engineering' skills of the human user are more critical than the software itself. He encourages users to focus on providing better information to the AI rather than searching for a 'magic' tool.

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