> ## 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

> Browse available LLM models and enable them in the AI Gateway. Filter by provider, capability, and pricing to find the right model.

## Enabling new Models

To see available Models and enable them for use, navigate to the **Models** page in **AI Gateway**.

<Frame caption="The Models page showing available models with pricing, features, and metadata columns.">
  <img src="https://mintcdn.com/orqai/5MZJQ0bWgWcedZzS/images/models-410.png?fit=max&auto=format&n=5MZJQ0bWgWcedZzS&q=85&s=e802133ed2760ebab7a1cf8355a6fd3b" alt="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." width="1745" height="1203" data-path="images/models-410.png" />
</Frame>

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 <kbd><Icon icon="arrow-up-arrow-down" /> Sort: Newest</kbd> 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 <kbd><Icon icon="table-columns" /> Columns</kbd> to show or hide individual columns.

<Check>
  Use the **Status Toggle** to **Enable** a model for use with the **AI Gateway**.
</Check>

### Filters

Use the modality tabs at the top of the list to scope models by type:

<kbd><Icon icon="table" /> All</kbd> <kbd><Icon icon="font" /> Text</kbd> <kbd><Icon icon="image" /> Image</kbd> <kbd><Icon icon="microphone" /> Audio</kbd> <kbd><Icon icon="wave-square" /> Speech</kbd> <kbd><Icon icon="hashtag" /> Embedding</kbd> <kbd><Icon icon="eye" /> Moderation</kbd> <kbd><Icon icon="arrow-up-arrow-down" /> Rerank</kbd>

The sidebar provides additional filters:

| Filter             | Description                                                                                                                                                                                             |
| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Location**       | Filter by region: Europe, United States, Global, APAC, Australia, Singapore                                                                                                                             |
| **Access**         | Toggle [**Zero data retention**](/enterprise/sovereign-ai#zero-data-retention) for ZDR-compliant providers, or [**BYOK**](/ai-gateway/providers-overview) for providers where an API key has been added |
| **Providers**      | Filter by LLM provider. See [Providers](/ai-gateway/providers-overview) 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**.

### Enable or Disable Models via the API

Models can also be enabled and disabled programmatically using the **Models** API. This is useful for CI/CD pipelines, automation scripts, or infrastructure-as-code workflows.

These endpoints sit on the [management plane](/management-apis/overview) and authenticate with a [Management Key](/ai-studio/organization/management-keys) that has `workspace-model` write access. A standard API Key cannot be granted the `workspace-model` domain and is rejected with **403**.

Enable a model:

<CodeGroup>
  ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}}
  curl --request POST \
    --url https://my.orq.ai/v2/workspace-models \
    --header "Authorization: Bearer $ORQ_MANAGEMENT_KEY" \
    --header "Content-Type: application/json" \
    --data '{ "model_id": "openai/gpt-5.6-sol" }'
  ```

  ```typescript TypeScript theme={"theme":{"light":"github-light","dark":"github-dark"}}
  import { Orq } from "@orq-ai/node";

  const orq = new Orq({ apiKey: process.env.ORQ_MANAGEMENT_KEY });

  await orq.models.enable({ modelId: "openai/gpt-5.6-sol" });
  ```

  ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
  from orq_ai_sdk import Orq
  import os

  orq = Orq(api_key=os.environ["ORQ_MANAGEMENT_KEY"])

  orq.models.enable(model_id="openai/gpt-5.6-sol")
  ```
</CodeGroup>

Disable a model:

<CodeGroup>
  ```bash cURL theme={"theme":{"light":"github-light","dark":"github-dark"}}
  curl --request DELETE \
    --url https://my.orq.ai/v2/workspace-models/openai/gpt-5.6-sol \
    --header "Authorization: Bearer $ORQ_MANAGEMENT_KEY"
  ```

  ```typescript TypeScript theme={"theme":{"light":"github-light","dark":"github-dark"}}
  import { Orq } from "@orq-ai/node";

  const orq = new Orq({ apiKey: process.env.ORQ_MANAGEMENT_KEY });

  await orq.models.disable({ modelId: "openai/gpt-5.6-sol" });
  ```

  ```python Python theme={"theme":{"light":"github-light","dark":"github-dark"}}
  from orq_ai_sdk import Orq
  import os

  orq = Orq(api_key=os.environ["ORQ_MANAGEMENT_KEY"])

  orq.models.disable(model_id="openai/gpt-5.6-sol")
  ```
</CodeGroup>

Both endpoints return **204** on success. Re-enabling an already-enabled model or disabling an already-disabled model is idempotent and also returns **204**.

When **Enforce enabled models** is turned on in [General Settings](/ai-studio/organization/workspace-settings), only models enabled through the dashboard or this API are available for routing. Requests that reference a non-enabled model are rejected.

For full request and response schemas, see [Enable model for workspace](/reference/models/enable-model-for-workspace) and [Disable model for workspace](/reference/models/disable-model-for-workspace).

### Restrict Model Access by Project

Once a model is enabled, workspace admins can see an <Icon icon="shield" /> **Access control** icon next to it. Select it to choose which projects can use the model, in one of two modes:

* **All projects** (default): every project in the workspace can use the model.
* **Custom**: each project gets its own on/off toggle, letting admins grant or revoke access per project.

Changes save immediately; there is no separate save action.

<Note>Access control is admin-only. Members with other roles see only the models an admin has approved within their chosen projects.</Note>

## Onboarding Private Models

Onboard private models by choosing <kbd className="key"><Icon icon="circle-plus" color="#fff" /> Model</kbd> 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 an OpenAI-compatible endpoint, **Azure AI Foundry**, or **AWS Bedrock**.

### Private Models Providers

<Expandable title="OpenAI Compatible">
  In the **AI Gateway** sidebar, go to **Models**, then click <kbd className="key"><Icon icon="circle-plus" color="#fff" /> Model</kbd> at the top-right and select **OpenAI Compatible**.

  <Steps>
    <Step title="Set the model type">
      Choose **Chat Completion**, **Completion**, **Embedding**, or **Image**.
    </Step>

    <Step title="Connect the endpoint">
      Enter the **Base URL** of the OpenAI-compatible endpoint, the **Model ID** the provider defines, and an **API Key**.
    </Step>

    <Step title="Identify the model">
      Set the **Model name** the gateway exposes, then fill in the token limits, per-token costs, and capabilities.
    </Step>
  </Steps>

  For the full field reference, see [OpenAI-compatible models](/ai-studio/integrations/providers/open-ai-like).
</Expandable>

<Expandable title="Azure AI Foundry">
  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://<resource>.openai.azure.com/openai/v1`                   | OpenAI-compatible deployments                                               |
  | Project endpoint      | `https://<resource>.services.ai.azure.com/api/projects/<project>` | 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.
  <Note>To learn more about the Azure AI Foundry deployment, see our [Provider Documentation](/ai-studio/integrations/providers/azure).</Note>

  <Steps>
    <Step title="Open Add Model">
      In the **AI Gateway** sidebar, go to **Models**, then click <kbd className="key"><Icon icon="circle-plus" color="#fff" /> Model</kbd> at the top-right and select **Azure**.
    </Step>

    <Step title="Enter credentials">
      Enter the **Base URL** and **API Key**.

      <img src="https://mintcdn.com/orqai/HHjqh-MIdaNoL6vT/images/azure-foundry.png?fit=max&auto=format&n=HHjqh-MIdaNoL6vT&q=85&s=bbf504783c350cfae387383255b8ea45" alt="Azure AI Foundry credentials panel showing the API key, Project endpoint, and Azure OpenAI endpoint at the top of the project homepage." width="5018" height="2490" data-path="images/azure-foundry.png" />

      <img src="https://mintcdn.com/orqai/4YNqGRNpuZNyo0_T/images/azure-foundry-410.png?fit=max&auto=format&n=4YNqGRNpuZNyo0_T&q=85&s=33d255754e482b449b349772cb7386e2" alt="Azure private model configuration form showing endpoint URL and API Key fields." width="628" height="445" data-path="images/azure-foundry-410.png" />
    </Step>

    <Step title="Fetch deployments">
      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 for routing requests through [Routing Rules](/ai-gateway/configuration/routing-rules).
    </Step>
  </Steps>

  Reference imported models in code using `<workspacename>@azure/<modelname>` (see [Referencing Private Models in Code](#referencing-private-models-in-code)).
</Expandable>

<Expandable title="AWS Bedrock">
  To add Bedrock models, first create an [Integration](/ai-studio/integrations/providers/aws-bedrock) for the AWS account.

  <Steps>
    <Step title="Open Add Model">
      In the **AI Gateway** sidebar, go to **Models**, click <kbd className="key"><Icon icon="circle-plus" color="#fff" /> Model</kbd> at the top-right and select **AWS Bedrock**.
    </Step>

    <Step title="Choose the model">
      Select the **AWS Integration**, enter the **Inference Profile ARN**, and confirm the **Region** parsed from the ARN.
    </Step>

    <Step title="Validate the connection">
      Click **Validate Connection**, then enter a display name and the model details.
    </Step>
  </Steps>
</Expandable>

<Expandable title="LiteLLM">
  To import LiteLLM models, first create an [Integration](/ai-studio/integrations/providers/litellm) for the LiteLLM instance. After creation, return to the **AI Gateway** and import models from the connected instance.

  <img src="https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6550edb6c1b14f32f561b6003ad29d42a6b4697c1d58ef31a26badf60ed3fae-Screenshot_2025-06-30_at_10.16.55.png?fit=max&auto=format&n=E8L3R46ivX7g9-QI&q=85&s=a8930b79f727e61ccdf6e0864db9229a" alt="LiteLLM model import screen showing how to select and import models from a connected LiteLLM instance." width="790" height="480" data-path="images/docs/a6550edb6c1b14f32f561b6003ad29d42a6b4697c1d58ef31a26badf60ed3fae-Screenshot_2025-06-30_at_10.16.55.png" />
</Expandable>

### Referencing Private Models in Code

When referencing private models through the SDKs, API, or [Supported Libraries](/ai-studio/integrations/frameworks/overview), the model is referenced by the following string: `<workspacename>@<provider>/<modelname>`.

> Example: `corp@azure/gpt-5.6-sol`

## Bring Your Own Key (BYOK)

To start using models, connect provider API keys via [**BYOK**](/ai-gateway/providers-overview) in the **AI Gateway** sidebar.