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.
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
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.
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.
- 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:
| Profile | Behaviour |
|---|---|
| Quality | Routes more requests to the strong model. Prioritises quality over cost. |
| Balanced | Distributes requests between both models based on prompt complexity. |
| Cost | Favours the economical model more aggressively to reduce spend. |
Recommended model pairs
These pairs combine high routing accuracy with significant cost ratios (over 10x), making them effective starting points for Auto Router configurations.| Strong Model | Budget Model |
|---|---|
| Google Gemini 2.5 Pro | Google Gemini 2.5 Flash |
| OpenAI GPT-5.1 | OpenAI GPT-4o Mini |
| Anthropic Claude Opus 4 | Google Gemini 3 Flash |
| OpenAI GPT-4o | OpenAI 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



