> ## 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 Gateway > Browse available LLM models and enable them in your AI Gateway workspace. Filter by provider, capability, and pricing to find the right model. ## Enabling new Models To see available Models and enable them for use, head to the **AI Gateway** section in **AI Studio** and open the **Models** page. Models page listing available LLM models with columns for name, input and output pricing, feature badges, release date, max output tokens, context length, and location. Each model displays its full name alongside a set of sortable columns: * **Name**: full model name and provider * **Input / Output pricing**: per-token cost for input and output * **Features**: capability badges indicating support for ZDR, BYOK, and other model-specific features * **Released**: the model's release date * **Max Output Tokens**: maximum tokens the model can generate per response * **Context Length**: total token window (input + output) * **Location**: the region where the model is served Use Sort: Newest to reorder by **Newest**, **Pricing** (low to high or high to low), **Context** (low to high or high to low), or **Max Output Tokens**. Use Columns to show or hide individual columns. Use the **Status Toggle** to **Enable** a model for use with the **AI Gateway**. ### Filters Use the modality tabs at the top of the list to scope models by type: All Text Image Audio Speech Embedding Moderation Rerank The sidebar provides additional filters: | Filter | Description | | ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Location** | Filter by region: Europe, United States, Global, APAC, Australia, Singapore | | **Access** | Toggle [**Zero data retention**](/docs/enterprise/sovereign-ai#zero-data-retention) for ZDR-compliant providers, or [**BYOK**](/docs/ai-studio/ai-gateway/connect-providers) for providers where an API key has been added | | **Providers** | Filter by LLM provider. See [Providers](/docs/ai-studio/ai-gateway/connect-providers) to configure API keys | | **Status** | Show Enabled or Disabled models | | **Features** | Filter by capability: Base64, Code Execution, Image Edit, JSON Mode, PDF, Reasoning, Streaming, Tool Calling, URL, Vision, Web Search | | **Context length** | Drag the range slider to filter by context window size (512 to 2M tokens) | | **Owner** | Filter between Public (**Orq.ai**-provided) and Private (onboarded) models | To enable a model, toggle it on. It will immediately be available to call with the **AI Gateway**. ## Onboarding Private Models Onboard private models by choosing Model at the top-right of the screen. This is useful when hosting a fine-tuned model or any model deployed on a private provider such as **Azure AI Foundry** or **Vertex AI**. ### Private Models Providers From the [**Azure AI Foundry**](https://ai.azure.com/) project homepage, copy the **API key** and one of the two endpoints shown at the top. **Orq.ai** accepts the following endpoints: | Endpoint type | Format | What it imports | | --------------------- | ----------------------------------------------------------------- | --------------------------------------------------------------------------- | | Azure OpenAI endpoint | `https://.openai.azure.com/openai/v1` | OpenAI-compatible deployments | | Project endpoint | `https://.services.ai.azure.com/api/projects/` | All deployments from publishers in the project (Anthropic, Cohere, and xAI) | Paste the endpoint URL exactly as shown in **Azure AI Foundry**. **Orq.ai** does not append any path suffix. To learn more about the Azure AI Foundry deployment, see our [Provider Documentation](/docs/ai-studio/integrations/providers/azure). In the **AI Gateway** sidebar, go to **Models**, then click Model at the top-right and select **Azure**. Enter the **Base URL** and **API Key**. Azure AI Foundry credentials panel showing the API key, Project endpoint, and Azure OpenAI endpoint at the top of the project homepage. Azure private model configuration form showing endpoint URL and API Key fields. Click **Fetch deployments** to automatically import all available deployments. The imported models appear in the **Models** list. Toggle each model **Enabled** before use. Enabled models are available in [Deployments](/docs/deployments/overview), [Agents](/docs/ai-studio/ai-engineering/build-agents), [Playground](/docs/playground/overview), and [Experiments](/docs/experiments/overview). Reference imported models in code using `@azure/` (see [Referencing Private Models in Code](#referencing-private-models-in-code)). In the **AI Gateway** sidebar, go to **Models**, then click Model at the top-right and select **Vertex AI**. Enter the JSON configuration from your Google Cloud project to make the model available on the platform. Google Vertex AI model configuration form showing the JSON configuration input to add a private model. For full Vertex AI setup instructions, see [Google Vertex AI](/docs/ai-studio/integrations/providers/vertex-ai). ### Referencing Private Models in Code When referencing private models through the SDKs, API, or [Supported Libraries](/docs/ai-studio/integrations/frameworks/overview), the model is referenced by the following string: `@/`. > Example: `corp@azure/gpt-4o-2024-05-13` ## Bring Your Own Key (BYOK) To start using models, connect your provider API keys via [**BYOK**](/docs/ai-studio/ai-gateway/connect-providers) in the **AI Gateway** sidebar.