Snowflake announced today that Google's Gemini 3 models are now running natively inside Snowflake Cortex AI. This means enterprises can use Google's latest AI models on their data without copying or moving it to another platform.
The integration includes both Gemini 3 Pro and Gemini Flash 2.5, available now in public preview through Cortex AI Functions. Support for Snowflake Intelligence and Cortex Agents is coming soon.
What This Solves
Moving enterprise data between platforms creates security risks, compliance headaches, and performance bottlenecks. By running Gemini models directly in Snowflake's governed environment, companies can build AI applications where their data already lives.
Gemini 3 Pro handles complex tasks that require deep reasoning across financial records, logs, product data, and documents. It's designed for production AI agents that need to understand context and make decisions based on structured and unstructured data.
Gemini Flash 2.5 focuses on speed and cost efficiency. It handles high-volume tasks like call summarization, invoice processing, and customer service interactions where you need fast results at scale.
How It Works
Developers can access Gemini models using SQL through Cortex AI Functions. Here's an example of analyzing financial documents:
SELECT
SNOWFLAKE.CORTEX.AI_COMPLETE(
'gemini-3-pro',
PROMPT(
'Review the following financial filing and summarize key revenue trends, margin changes, and risk factors: {0}',
filing_text
)
) AS financial_summary
FROM financial_documents;
The models support cross-region inference, so you can run them across all supported clouds by enabling GCP_US or ANY_REGION in your admin settings.
Real-World Use Cases
BlackLine is using Gemini models embedded in Snowflake to build agentic AI for finance and accounting teams. Jeremy Ung, BlackLine's CTO, says they're moving beyond simple automation to create AI that actively partners with financial professionals on complex processes.
Fivetran CEO George Fraser notes that tasks that used to take weeks of custom development now happen in days. Teams can ask questions and get answers from their business data without building custom integrations.
Broader Partnership
This announcement deepens the relationship between Snowflake and Google Cloud beyond just AI models. The companies are aligning their sales teams, expanding product integrations, and making Snowflake available through Google Cloud Marketplace.
Snowflake is also expanding its Google Cloud footprint. It recently launched in Saudi Arabia and will launch in Melbourne, Australia in early 2026.
The integration includes connections to Google Cloud's Vertex AI platform and BigQuery, giving customers more options for how they build and deploy AI applications.
What Developers Should Know
Gemini joins other models from Anthropic, Meta, and OpenAI already available in Cortex AI. This gives teams flexibility to choose the right model for each task without changing their data architecture.
The focus on running models inside Snowflake's governance perimeter means you maintain security controls while experimenting with different AI capabilities. You're not trading off between innovation and compliance.
[Christian Kleinerman][1], Snowflake's EVP of Product, puts it simply: "By combining Google Cloud's industry leadership with Snowflake's ability to bring AI directly to enterprise data, we're empowering customers to move faster, innovate more freely and redefine what's possible through data and AI."
For organizations already running on Snowflake and Google Cloud, this reduces the complexity of adding AI capabilities to existing data workflows. For those evaluating platforms, it's another data point in favor of keeping your data stack consolidated.
[1]: https://www.linkedin.com/in/christian-kleinerman-a973102/
