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Models

AI Search uses models at multiple stages. You can configure which models are used, or let AI Search automatically select a smart default for you.

Models usage

AI Search leverages Workers AI models in the following stages:

  • Image to markdown conversion (if images are in data source): Converts image content to Markdown using object detection and captioning models.
  • Embedding: Transforms your documents and queries into vector representations for semantic search.
  • Query rewriting (optional): Reformulates the user’s query to improve retrieval accuracy.
  • Generation: Produces the final response from retrieved context.

Model providers

All AI Search instances support models from Workers AI. You can use other providers (such as OpenAI or Anthropic) in AI Search by adding their API keys to an AI Gateway and connecting that gateway to your AI Search.

To use AI Search with other model providers:

  1. Add provider keys to AI Gateway
  • Go to AI > AI Gateway in the dashboard.
  • Select or create an AI gateway.
  • In Provider Keys, choose your provider, click Add, and enter the key.
  1. Connect the gateway to AI Search
  • When creating a new AI Search, select the AI Gateway with your provider keys.
  • For an existing AI Search, go to Settings and switch to a gateway that has your keys under Resources.
  1. Select models
  • Embedding model: Only available to be changed when creating a new AI Search.
  • Generation model: Can be selected when creating a new AI Search and can be changed at any time in Settings.

AI Search supports a subset of models that have been selected to provide the best experience. See list of supported models.

Smart default

If you choose Smart Default in your model selection, then AI Search will select a Cloudflare recommended model and will update it automatically for you over time. You can switch to explicit model configuration at any time by visiting Settings.

Per-request generation model override

While the generation model can be set globally at the AI Search instance level, you can also override it on a per-request basis in the AI Search API. This is useful if your RAG application requires dynamic selection of generation models based on context or user preferences.

Model deprecation

AI Search may deprecate support for a given model in order to provide support for better-performing models with improved capabilities. When a model is being deprecated, we announce the change and provide an end-of-life date after which the model will no longer be accessible. Applications that depend on AI Search may therefore require occasional updates to continue working reliably.

Model lifecycle

AI Search models follow a defined lifecycle to ensure stability and predictable deprecation:

  1. Production: The model is actively supported and recommended for use. It is included in Smart Defaults and receives ongoing updates and maintenance.
  2. Announcement & Transition: The model remains available but has been marked for deprecation. An end-of-life date is communicated through documentation, release notes, and other official channels. During this phase, users are encouraged to migrate to the recommended replacement model.
  3. Automatic Upgrade (if applicable): If you have selected the Smart Default option, AI Search will automatically upgrade requests to a recommended replacement.
  4. End of life: The model is no longer available. Any requests to the retired model return a clear error message, and the model is removed from documentation and Smart Defaults.

See models are their lifecycle status in supported models.

Best practices

  • Regularly check the release note for updates.
  • Plan migration efforts according to the communicated end-of-life date.
  • Migrate and test the recommended replacement models before the end-of-life date.