Hi @abhijit007,

Both Genie and Agent Bricks are built as managed, model‑flexible services rather than being tied to a single fixed LLM.

Genie is implemented as a compound AI system that uses LLMs plus Unity Catalog metadata, example SQL, and space instructions to translate natural language into SQL and answers. When partner-powered AI features are enabled, Genie uses models hosted by Azure OpenAI / Azure AI Services as the underlying LLM provider. Databricks can upgrade or change the specific base model over time as part of the managed service.

Agent Bricks (including Supervisor Agent) is model‑agnostic. It uses Mosaic AI Model Serving and AI Gateway to work with foundation models available in Unity Catalog (the system.ai schema) or other configured model endpoints. Supervisor Agent also requires access to foundation models in system.ai and the databricks-gte-large-en embedding model. The supervisor logic itself runs on Databricks‑hosted foundation models, and the exact model choice can evolve over time as Databricks optimizes quality and performance.

There's more detailed information in the links I shared earlier.

Does that answer your question?

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