> ## Documentation Index
> Fetch the complete documentation index at: https://allhandsai-docs-custom-tools-agent-server-extra-path.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Language Model (LLM) Settings

> This page goes over how to set the LLM to use in OpenHands, including LLM profiles for switching models during conversations.

## Overview

The LLM settings allows you to bring your own LLM and API key to use with OpenHands. This can be any model that is
supported by litellm, but it requires a powerful model to work properly.
[See our recommended models here](/openhands/usage/llms/llms#model-recommendations). You can also configure some
additional LLM settings on this page.

## Basic LLM Settings

The most popular providers and models are available in the basic settings. Some of the providers have been verified to
work with OpenHands such as the [OpenHands provider](/openhands/usage/llms/openhands-llms), Anthropic, OpenAI and
Mistral AI.

1. Choose your preferred provider using the `LLM Provider` dropdown.
2. Choose your favorite model using the `LLM Model` dropdown.
3. Set the `API Key` for your chosen provider and model and click `Save Changes`.

This will set the LLM for all new conversations. If you want to use this new LLM for older conversations, you must first
restart older conversations.

## Advanced LLM Settings

Toggling the `Advanced` settings, allows you to set custom models as well as some additional LLM settings. You can use
this when your preferred provider or model does not exist in the basic settings dropdowns.

1. `Custom Model`: Set your custom model with the provider as the prefix. For information on how to specify the
   custom model, follow [the specific provider docs on litellm](https://docs.litellm.ai/docs/providers). We also have
   [some guides for popular providers](/openhands/usage/llms/llms#llm-provider-guides).
2. `Base URL`: If your provider has a specific base URL, specify it here.
3. `API Key`: Set the API key for your custom model.
4. Click `Save Changes`

### Memory Condensation

The memory condenser manages the language model's context by ensuring only the most important and relevant information
is presented. Keeping the context focused improves latency and reduces token consumption, especially in long-running
conversations.

* `Enable memory condensation` - Turn on this setting to activate this feature.
* `Memory condenser max history size` - The condenser will summarize the history after this many events.

## LLM Profiles

LLM profiles allow you to save multiple LLM configurations and switch between them, even during an active conversation.
This is useful when you want to use different models for different tasks—for example, a faster model for simple tasks
and a more powerful model for complex reasoning.

### Creating an LLM Profile

Profiles are automatically created when you save a configuration on the LLM settings page. To create a new profile:

1. Navigate to `Settings > LLM`.
2. Configure your desired LLM provider, model, and API key.
3. Click `Save Changes`.

A new profile will be created with your configuration. The most recently saved profile becomes the active profile
for new conversations.

Alternatively, you can click the `Add LLM Profile` button in the Available Profiles section to create a new profile
directly.

### Managing LLM Profiles

You can manage your saved profiles in the `Available Profiles` section of the LLM settings page. Each profile shows:

* **Profile name**: A unique identifier for the configuration
* **Model**: The LLM model associated with the profile
* **Active badge**: Indicates which profile is currently active

Click the menu icon (three dots) on any profile to access these actions:

* **Edit**: Modify the profile's LLM configuration
* **Rename**: Change the profile name
* **Set as Active**: Make this profile the default for new conversations
* **Delete**: Remove the profile

<Note>
  You can save up to 10 LLM profiles per account. Delete unused profiles if you need to create new ones.
</Note>

### Switching Profiles During a Conversation

One of the most powerful features of LLM profiles is the ability to switch models mid-conversation without losing context.
This allows you to:

* Start with a fast, cost-effective model for initial exploration
* Switch to a more powerful model when the task requires deeper reasoning
* Use specialized models for specific types of tasks

To switch profiles during an active conversation:

1. Look for the **profile selector button** in the chat input area. It displays the name of the currently active profile.
2. Click the button to open the profile menu.
3. Select the profile you want to switch to.

The conversation will continue with the new model, maintaining all previous context and history. The switch takes effect
immediately for subsequent messages.

<Tip>
  The profile selector shows a checkmark next to the currently active profile. If no profile matches the running model,
  the button will show "Select a model" as a placeholder.
</Tip>

### Switching Profiles with the `/model` Slash Command

You can also list and switch profiles directly from the chat input using the `/model` slash command:

* `/model` — Lists your saved LLM profiles, including which one is active and whether each profile has an API key set.
* `/model <name>` — Switches the conversation to the profile with the given name.

This is equivalent to using the profile selector button and works without leaving the chat.

### How Profile Switching Works

When you switch profiles during a conversation:

1. The new LLM configuration is loaded from your saved profile
2. The conversation context (all previous messages and actions) is preserved
3. Future messages are processed using the new model
4. The conversation metadata is updated to reflect the new model

This seamless switching allows you to leverage different models' strengths without starting a new conversation or
losing your progress.

### Best Practices for Using LLM Profiles

* **Name profiles descriptively**: Use names like "Claude Sonnet - Fast" or "GPT-4 - Complex Tasks" to easily
  identify which profile to use.
* **Create task-specific profiles**: Set up profiles optimized for different workflows, such as code review,
  documentation, or debugging.
* **Keep API keys updated**: Ensure each profile has a valid API key.
* **Test before critical work**: When switching profiles mid-conversation, send a simple test message to confirm
  the new model is responding correctly.