Local LLM - Keeping us down

Discussions
1

I would gladly pay $400 - $600 if I could have a version of cursor that allowed me to use a Local LLM. It’s a sad situation.

2

Yes, you can use the Cursor AI IDE with a locally run LLM, but it’s not a straightforward native feature and typically requires a workaround. Here’s a breakdown:
How it generally works:

  • Local LLM Setup: You’ll need to have your LLM running locally. Popular options for this include using tools like Ollama or LM Studio, which allow you to download and serve various open-source models.
  • Exposing the Local LLM: Cursor doesn’t directly recognize localhost addresses for LLM endpoints. Therefore, you need to expose your local LLM to an external URL. Tools like ngrok are commonly used for this. ngrok creates a secure tunnel from a public URL to your local machine.
  • Cursor Configuration:
    • In Cursor’s settings, you’ll typically go to the “Models” or “AI Settings” section.
    • You’ll need to enable the option to use a custom OpenAI API endpoint.
    • You’ll then input the ngrok URL (followed by /v1 to mimic the OpenAI API structure) as the custom API base URL.
    • You might need to provide a placeholder API key (any random string often works for local setups not requiring actual authentication with OpenAI).
    • You’ll then add your local model’s name as it’s recognized by your local LLM server (e.g., the model tag from Ollama).
    • It’s usually recommended to disable other cloud-based models in Cursor to ensure it uses your local setup.
      Important Considerations:
  • Not Officially Supported for all Setups: While a workaround exists, Cursor’s official documentation states they “do not provide support for custom local LLM setups or other API formats” beyond those compatible with the OpenAI API format.
  • Online Requirement (for ngrok): Using ngrok means that while the LLM processing happens locally, your computer still needs an internet connection for Cursor to communicate with the LLM via the ngrok tunnel.
  • Cursor’s Server-Side Processing: Some users in community forums have pointed out that a lot of Cursor’s “magic” (like indexing and some pre-processing) might still happen on Cursor’s servers before hitting your LLM. This could be a concern if your primary reason for using a local LLM is 100% data privacy with no external calls. However, the core inference (the actual text generation by the LLM) would happen locally.
  • Performance: The performance will depend on your local hardware (CPU, GPU, RAM) and the size and efficiency of the LLM you are running.
  • Evolving Feature: The specifics of how to configure this can change with new Cursor updates. It’s always a good idea to check recent community discussions or guides.
    In summary: While not a built-in, one-click feature, tech-savvy users have found ways to make Cursor work with local LLMs, primarily by making the local LLM accessible via a public-facing URL using tools like ngrok and configuring Cursor to use this as a custom OpenAI-compatible endpoint.

By Gemini 2.5Pro

1 Like
3

I have seen a post here with this same info.
I just don’t want to deal with “work arounds” … and dude, trust me when I say I super appreciate you taking the time to share this with me.
Do you have linkedin? I would like to talk with you about some other Cursor stuff.
Add me: /in/uxuiburnett/

4

Issue with this approach is that conversational data is still being routed to the Cursor cloud.

1 Like