Databricks said OpenAI's foundational models will be available in the Databricks Data Intelligence Platform and Agent Bricks natively in a partnership worth $100 million.
The deal highlights how OpenAI is expanding the distribution for its ChatGPT family of models beyond Microsoft and direct access.
In recent weeks, OpenAI has become available on Oracle Cloud Infrastructure. The company's open weight models are now available on AWS. Snowflake added OpenAI models via an expanded partnership with Microsoft.
Databricks said OpenAI models, including GPT-5, are available to more than 20,000 customers. GPT-5 will also be the flagship model for all Databricks customers.
- Databricks valued at $100 billion
- Databricks natively integrates Google Cloud Gemini models
- Databricks launches Mosaic Agent Bricks, Lakeflow Designer, Lakehouse
By offering OpenAI models natively, Databricks customers will be able to build AI agents closer to where data lives with no extra movement.
Key points about the Databricks-OpenAI deal:
- Databricks can get OpenAI models via SQL or API.
- Databricks customers have access to high-capacity processing across the latest OpenAI models.
- Agent Bricks will tune and optimize GPT-4 and gpt-oss for accuracy.
- Databricks Unity Catalog will provide governance and observability for OpenAI models.
- The two companies will optimize OpenAI models for enterprise use case.
Databricks said GPT-5, GPT-5 mini and GPT-5 nano will be available natively in Databricks across AWS, Microsoft Azure and Google Cloud in the near future.
Holger Mueller, an analyst at Constellation Research, said the OpenAI-Databricks partnership appears to be a win-win situation.
"This partnership emancipates Databricks from the cloud providers who have already partnered with OpenAI - and takes a differentiator for the cloud vendors away. Cloud vendors' data lake houses work seamlessly with their AI frameworks. CxOs now have options on how to build their AI powered next-gen apps.
If Databricks plays this well it becomes the multi cloud data and LLM foundation for enterprises. Being multi cloud has ways paid off at any level of the stack - and there is no reason for it not to work for Databricks. What is unique is that this touches more layers of the stack."
