How to Use Local Models With Cursor.ai?
Using local models with Cursor.ai is possible, but it does not work the way most people initially expect. Cursor cannot connect directly to a model running on localhost or a private LAN. A public HTTPS endpoint is required, and Cursor still sits in the request path. Once you understand that constraint, the setup becomes much clearer and more predictable.
If you already work with AI tools or come from an AI Certification background, this setup will feel familiar. Cursor treats local models as custom OpenAI-compatible endpoints rather than true offline models.
What does “local models with Cursor.ai” actually mean?
Local models with Cursor.ai means the model runs on your own machine, but Cursor talks to it through a public HTTPS URL. Cursor does not talk to localhost directly.
The request flow looks like this:
Cursor → public HTTPS endpoint → tunnel or gateway → your local model server
So the compute is local, but the coordination is not fully local.
Why can’t Cursor connect to localhost directly?
Cursor builds prompts and manages context on its own servers. Because of that architecture, Cursor requires a publicly reachable HTTPS endpoint for any custom model.
Cursor staff and community replies consistently confirm that direct localhost or private IPs are not supported. This is not a bug. It is a design choice tied to how Cursor works today.
Where do you configure local models in Cursor?
Everything happens in Cursor Settings under Models.
You add a custom model and configure two main fields:
An OpenAI API key
An override OpenAI base URL
Most users report this setup is done through the UI, not config files. Cursor expects the endpoint to behave like an OpenAI-compatible API.
Which local model servers actually work?
Almost everyone uses a local server that speaks the OpenAI API format.
Can you use Ollama with Cursor?
Yes. Ollama is one of the most common choices.
Ollama exposes an OpenAI-compatible API locally, usually at http://localhost:11434/v1. Cursor cannot use this directly, but once it is exposed through HTTPS, it works.
Can you use LM Studio with Cursor?
Yes. LM Studio also runs a local OpenAI-compatible server, commonly at http://localhost:1234/v1.
From Cursor’s point of view, LM Studio and Ollama look the same once they are reachable through a public HTTPS URL.
Developers who come from a systems or infrastructure-focused Tech Certification background often prefer this approach because it keeps inference under their control.
How do you bridge Cursor to a local model?
This is the part most people miss.
Because Cursor requires HTTPS, you need a bridge between Cursor and your local server.
The most common options are:
ngrok to expose your local server over HTTPS
A public gateway or reverse proxy pointing to your local machine
LiteLLM acting as an OpenAI-compatible proxy in front of Ollama or LM Studio
Cursor staff have explicitly mentioned ngrok as a supported workaround in community replies.
What problems do people keep running into?
Several issues come up again and again.
Why does Cursor say the model is not available?
Cursor validates model names. If your local model name does not match what Cursor expects, you may see errors like “not available on your plan.”
Some users work around this by matching known model identifiers or using override options when available.
Why does HTTPS matter so much?
Cursor does not accept non-HTTPS base URLs. Plain HTTP endpoints fail even if everything else is correct. This is why tunnels that provide HTTPS are required.
Do plans affect custom local models?
User reports suggest that plan status can affect whether custom endpoints work smoothly.
Some users say local endpoints worked during a Pro trial and stopped on a free plan. Others mention needing to validate with a real OpenAI key first, then switching the base URL. These are user-observed behaviors, not officially documented guarantees.
Why do tools or agents break on local models?
Some local models handle basic chat fine but fail during tool calls or agent-style planning. This is a limitation of the model, not Cursor itself.
If your workflow relies on tools, function calling, or agents, expect trial and error.
What is the actual benefit of using local models with Cursor?
The upside is local inference speed and more control over data and compute. Some users also observe that local runs do not consume Cursor usage the same way built-in models do, although this is based on community observation.
From a product and cost perspective, this setup is often discussed alongside Marketing and Business Certification topics because it affects scaling, pricing, and internal tooling decisions.
Is Cursor an offline-first tool?
No.
Cursor can work with local inference, but it is not offline-first. Cursor servers remain part of the request path, and a public endpoint is required.
If you want true offline AI coding, Cursor is not built for that today.
Conclusion
You can use local models with Cursor.ai, but only through a public HTTPS endpoint. Most setups rely on Ollama or LM Studio, exposed through ngrok or a similar gateway, often with LiteLLM in front.
Once you accept that Cursor still sits in the middle, the setup makes sense. It is local compute paired with a cloud-coordinated editor, not a fully local system.