Onyx Code vs Cursor

The short answer

Cursor runs the model on Cursor’s servers. Onyx Code runs the model on your machine. Nearly every other difference between the two follows from that one.

The one real difference: where the model runs

Cursor is a cloud product with an editor attached. Your prompt, the surrounding code and the retrieved context are sent to Cursor, which calls a model provider and streams the answer back. That is what makes its frontier models feel as good as they do, and it is also what makes the question of what leaves your machine unavoidable.

Onyx Code ships a llama.cpp inference engine inside the app and a model tuned to your hardware. Chat, autocomplete, next-edit prediction, codebase search and the agent all run against that engine on localhost. There is no account, no sign-in and no server to configure, and you can pull the network cable mid-completion.

If you want the cloud models anyway, Onyx Code takes your own OpenAI, Anthropic, Groq or Mistral key on the Free tier and calls them directly, so nothing is proxied through us. The default stays local; the cloud is a choice you make per task.

Feature comparison

Onyx rows are sourced from the Free versus Pro reference that ships with the product. Where a capability is Pro, it says so.

Both editors are VS Code forks, so both use the Open VSX registry rather than Microsoft’s marketplace. That is a real limitation and it applies equally to both.

What Cursor does better

This section is here because a comparison page without it is an advertisement. These are real advantages, and for a lot of people they are the deciding ones.

• Model quality on hard problems. A frontier model reasons better than a 7B-class model running on your laptop. For a subtle refactor across an unfamiliar codebase, Cursor will more often be right first time. We do not claim otherwise, which is why Onyx Code lets you bring your own cloud key when a task deserves one.
• Tab completion. Cursor Tab is excellent, and it is trained on a scale of real edit data we cannot match.
• Long autonomous runs.The bigger the model, the further an agent can go before it needs a human. Cursor’s agent holds up over longer tasks than a local model does.
• Team and enterprise plumbing. Seat management, org policy, SOC 2, and zero-retention agreements with model providers. Onyx Code sells a one-time personal licence today and has none of that yet.
• Pace. A funded team ships features faster than a small one. If you want the newest thing the week it appears, that is not us.

Who should switch

Situations, not personas. If none of these is you, Cursor is a good product and you should keep using it.

• Your employer will not let you paste code into a cloud service, and you have been coding without AI help because of it.
• You work on a client codebase under an agreement that names third-party processors, and adding one means a conversation with legal that you would rather not have.
• You need to show an auditor what an AI tool read and wrote in your repository. The Activity Log and its PDF export exist for exactly that conversation.
• You code on planes, trains, a boat, a site with no signal, or a network that blocks everything interesting.
• You are tired of subscriptions and want the tool to keep working when you stop paying attention to it.
• Your machine has a decent GPU or Apple Silicon and it is sitting idle while you rent someone else’s.

What each actually costs

Cursor is $20 a month on the Pro plan, with a free Hobby tier and larger plans above it. Onyx Code has a Free tier that is a complete editor with local AI, and a Pro licence at $39 once, valid on three of your machines, with major version upgrades included.

The honest framing is not that one is cheap and the other expensive. A subscription buys you someone else’s GPUs and the best models on them, every month. A one-time licence buys software that runs on hardware you already own. The first is better value if you want frontier reasoning all day; the second is better value if the work you want help with is autocomplete, questions about your own codebase, and mechanical multi-file edits, which is most of the day for most people.

Questions people ask before switching

Is Onyx Code open source?

The editor is built on VS Code OSS, which is MIT licensed. The AI layer on top is proprietary, and Pro is a paid licence. We say that plainly rather than burying it, because the alternative is you finding out later.

Can I keep my VS Code extensions?

Most of them. Like every VS Code fork, including Cursor, Onyx Codeuses the Open VSX registry because Microsoft’s marketplace is not licensed for forks. The first-run wizard imports your VS Code settings and tells you by name which of your extensions are not on Open VSX, and there is an install-from-VSIX path for the rest.

Will a local model be fast enough?

For autocomplete and next-edit prediction, yes, and often faster than a round trip to a data centre. The bundled engine uses Metal on Apple Silicon and Vulkan on NVIDIA, AMD and Intel GPUs, with an in-app Auto, GPU or CPU switch. The model is chosen for your hardware during setup rather than left to you to guess.

Do I have to install Ollama or LM Studio first?

No. The engine and a first model come with the app, which is the main practical difference between Onyx Code and the do-it-yourself local stacks. Connecting to an external Ollama, LM Studio or remote inference server is supported too, on the Pro tier.

Can I use both?

Plenty of people will. Keep Cursor for the work that benefits from a frontier model, and use Onyx Code for the repositories that are not allowed anywhere near one. They import the same settings and read the same .cursorrules file.