> ## Documentation Index
> Fetch the complete documentation index at: https://docs.hymalaia.com/llms.txt
> Use this file to discover all available pages before exploring further.

# LM Studio

> Using LM Studio with Hymalaia

## Guide

Configure Hymalaia to use models served by [LM Studio](https://lmstudio.ai/).

Hymalaia has a built-in integration with LM Studio that auto-discovers your loaded models,
including their capabilities (vision, reasoning) and context length.

<Steps>
  <Step title="Setup LM Studio and Load Your Models">
    Download LM Studio from [lmstudio.ai](https://lmstudio.ai/) and load the models you want to use.

    Start the LM Studio local server:

    ```bash theme={null}
    lms server start --port 1234
    ```

    LM Studio runs on port `1234` by default.

    <Tip>
      For best results, use a model with strong instruction-following and tool-use capabilities (e.g., Qwen 3.5).
    </Tip>

    If LM Studio is running on a different machine tha Hymalaia,
    make sure the server is accessible from the Hymalaia host (e.g., `http://<lm-studio-host>:1234`).

    <Info>
      **Running Hymalaia in Docker on the same machine as LM Studio?**

      By default, LM Studio binds only to `127.0.0.1`, which is unreachable from inside a Hymalaia container. To fix:

      * In LM Studio's **Developer** tab, enable **"Serve on Local Network"** (or set the host to `0.0.0.0`) and restart the server.
      * Use `http://host.docker.internal:1234` as the **API Base URL** instead of `http://localhost:1234`.

      See [LM Studio's docs](https://lmstudio.ai/docs/developer/core/server/serve-on-network) for more details.
    </Info>
  </Step>

  <Step title="Navigate to Language Models">
    Access the Admin Panel from your user profile icon, then navigate to **Configuration → Language Models**.
  </Step>

  <Step title="Configure LM Studio">
    Select **LM Studio** from the available providers.

    Give your provider a **Display Name**.

    Set the **API Base URL** to your LM Studio server address (e.g., `http://localhost:1234`).

    If Hymalaia is running in Docker on the same machine as LM Studio,
    use `http://host.docker.internal:1234` instead — `localhost` inside the container points to the container itself,
    not your host.
    Make sure LM Studio is set to **"Serve on Local Network"** (see the Info callout in the previous step).

    Hymalaia will automatically connect and discover your loaded models.

    <img className="rounded-xl shadow-md mx-auto" src="https://mintcdn.com/hymalaia/8ykKHOjeXvJ7RJZr/images/ai-models/lm_studio_config.png?fit=max&auto=format&n=8ykKHOjeXvJ7RJZr&q=85&s=0f0d7ecdc86a3f1af68bf45334d7d692" alt="LM Studio Provider Configuration" width="1730" height="1544" data-path="images/ai-models/lm_studio_config.png" />
  </Step>

  <Step title="Choose Visible Models">
    In the **Advanced Options**, you will see a list of all models available from this provider.
    You may choose which models are visible to your users in Hymalaia.

    Setting visible models is useful when a provider publishes multiple models and versions of the same model.
  </Step>

  <Step title="Designate Provider Access">
    Lastly, decide whether the provider should be public to all users in Hymalaia.

    If set to private,
    the provider's models will be available to Admins and User Groups you explicitly assign the provider to.
  </Step>
</Steps>


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.