Deploying LLMs on Databricks Model Serving

Databricks Model Serving provides a single solution to deploy any AI model without the need to understand complex infrastructure. This means you can deploy any natural language, vision, audio, tabular, or custom model, regardless of how it was trained - whether built from scratch, sourced from open-source, or fine-tuned with proprietary data. Simply log your model with MLflow, and we will automatically prepare a production-ready container with GPU libraries like CUDA and deploy it to serverless GPUs. Our fully managed service will take care of all the heavy lifting for you, eliminating the need to manage instances, maintain version compatibility, and patch versions. The service will automatically scale instances to meet traffic patterns, saving infrastructure costs while optimizing latency performance.