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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.
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 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

Referencing Private Models in Code

When referencing private models through our SDKs, API or Supported Libraries, the model is referenced by the following string: <workspacename>@<provider>/<modelname>.
Example: corp@azure/gpt-4o-2024-05-13

Auto Router

The Auto Router is a virtual model that automatically routes each request to the most appropriate model for it. Simple requests go to a cheaper model; requests that benefit from higher quality go to a stronger one. The routing decision is based on predicted human preference, computed in real time from the content of the prompt. To create an Auto Router, click Add Model at the top-right of the AI Router and select Auto Router from the dropdown.
Auto Router configuration
Configure the following fields:
  • Model ID: a unique identifier for this router. Lowercase letters, numbers, and hyphens only (e.g. my-auto-router). This is how you reference the router in your deployments.
  • Strong Model: the higher-quality model to route to when the prompt warrants it.
  • Economical Model: the cheaper model to use for simpler requests.
  • Profile: controls how aggressively the router favours the strong model:
ProfileBehaviour
QualityRoutes more requests to the strong model. Prioritises quality over cost.
BalancedDistributes requests between both models based on prompt complexity.
CostFavours the economical model more aggressively to reduce spend.
Once created, the Auto Router appears in your AI Router and can be selected anywhere a model is accepted: Deployments, Agents, Playground, and Experiments.
Models from the same family or tier work well together (e.g. Claude Sonnet and Gemini Flash). Very large capability gaps reduce the effectiveness of routing.
These pairs combine high routing accuracy with significant cost ratios (over 10x), making them effective starting points for Auto Router configurations.
Strong ModelBudget Model
Google Gemini 2.5 ProGoogle Gemini 2.5 Flash
OpenAI GPT-5.1OpenAI GPT-4o Mini
Anthropic Claude Opus 4Google Gemini 3 Flash
OpenAI GPT-4oOpenAI GPT-4o Mini

Referencing an Auto Router in Code

When using an Auto Router through the SDKs, API, or Supported Libraries, reference it by the following string: <workspacename>@orq/<model-id>.
Example: acme@orq/my-auto-router