> ## Documentation Index > Fetch the complete documentation index at: https://docs.orq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Models | AI Router > Browse available LLM models and enable them in your AI Router workspace. Filter by provider, capability, and pricing to find the right model. ## Enabling new Models To see your available Models and enable them for use, head to the **AI Router** section in **AI Studio**, open the **Models** page. Searching through all available models. Each model includes a detailed overview of its capabilities, performance, and configuration.\ You can easily compare models across multiple columns, such as: * **Provider and Model Type** — to identify the source and intended use of the model * **Modality** — to see whether the model supports text, image, or both for input and output * **Intelligence and Speed Ratings** — to quickly assess performance tradeoffs * **Token and Pricing Data** — to understand input and output costs * **Region and Release Date** — to identify where and when models are available These columns help you make informed decisions when selecting a model for your experiments or deployments. You can also directly access **AI Router code snippets** from each model card, allowing you to copy ready to use integration examples for immediate use in your application or deployment. Use the **Status Toggle** to **Enable** a model for use with the AI Router. ### Filters You have access to *multiple filters* to search models: * **Providers** let you filter which LLM provider you want to see. * **Model Type** lets you decide on which type of model you intend to see (Chat, Completion, Embedding, Rerank, Vision). * **Active** lets you filter on enabled or disabled models in your workspace. * **Owner** lets you filter between Orq.ai provided models and private models. * **API Key Status** lets you filter models for which you have added an API key. You can now filter by **Location, Modality, Providers, and Features** to find the right model for your use-case. Filter Router You can preview the pricing of each model within the **Pricing column**. To enable a model, **toggle** it on. It will immediately be available to call with the AI Router. ## Using your own API keys To start using models, you have to bring your own keys, head to the [**Providers**](/docs/router/providers-overview) tab to use your own API keys with the supported providers. ## Onboarding Private Models You can onboard private models by choosing **Add Model** at the top-right of the screen. This can be useful when you have a model fine-tuned you want to use. ### Private Models Providers Here is an example configuration for an *Azure* model, entering the endpoint and API Key will make your private model available on the platform. Here an example configuration for an _Azure_ model, entering the endpoint and API Key will make your private model available on the platform. Here is an example configuration for a **Google Vertex AI** model, enter the JSON configuration to make a private model available on the platform. Google Vertex AI model configuration form showing the JSON configuration input to add a private model. LiteLLM To import LiteLLM models, first create an [Integration](/docs/integrations/providers/litellm) to your LiteLLM instance. Once created, come back to the AI Router and Import models from your Instance. LiteLLM model import screen showing how to select and import models from a connected LiteLLM instance. ### Referencing Private Models in Code When referencing private models through our SDKs, API or [Supported Libraries](/docs/proxy/frameworks/overview), the model is referenced by the following string: `@/`. > Example: `corp@azure/gpt-4o-2024-05-13` ## Auto Router Route requests automatically between a Strong Model and an Economical Model based on task complexity. See the Auto Router page for setup, profiles, and recommended model pairs.