Google Gemini now runs natively on Oracle’s cloud infrastructure

Google has partnered with Oracle to bring its Gemini AI models directly to Oracle Cloud Infrastructure, marking a significant departure from typical exclusive cloud-AI partnerships. This integration allows enterprise customers to access Gemini’s advanced language and multimodal capabilities natively within Oracle’s cloud environment, bypassing traditional barriers to cross-cloud AI adoption and positioning Oracle as a multi-vendor AI platform provider.

What you should know: Oracle customers can now consume Gemini models as part of the Oracle Cloud Infrastructure Generative AI suite, not just as external APIs.

• The partnership starts with Gemini 2.5 and plans to expand to include models for image, video, audio, and industry-specific solutions like MedLM for healthcare.
• Customers can use Oracle Universal Credits to pay for Google AI services, streamlining procurement for large organizations.
• Technical teams can embed Gemini’s capabilities directly into Oracle-powered applications without moving workloads or data off Oracle infrastructure.

How it works: The integration enables AI agents to handle business process automation, data enrichment, and workflow integration using Gemini’s advanced reasoning capabilities.

• Financial data in Oracle databases can be queried and augmented through chat interfaces powered by Gemini for rapid insights.
• Gemini-augmented features will be embedded into future Oracle Fusion Cloud Applications, including HR, finance, and supply chain solutions.
• The models run on Google’s infrastructure but are routed through Oracle’s secure gateways.

The big picture: Oracle is executing a multi-vendor AI strategy that contrasts sharply with competitors’ exclusive partnerships.

• While Microsoft focuses on OpenAI and Amazon Web Services (AWS) on Anthropic, Oracle has partnered with xAI, Cohere, Meta’s Llama family, and now Google’s Gemini.
• This approach allows Oracle customers to benchmark different models and select the best fit without wholesale cloud migration.
• For Google, the partnership opens doors to enterprise accounts that rely on Oracle for business-critical applications and regulated datasets.

Practical use cases: Several enterprise applications become more actionable under the new integration.

• AI-powered document understanding embedded directly into supply chain management workflows.
• Leveraging Gemini’s large context windows for software development assistance within Oracle’s DevOps environments.
• Chat-driven financial reporting or transaction audits that combine real business data with AI summarization.

What to watch: The multi-cloud approach introduces complexity that enterprises must navigate carefully.

• Questions remain about latency, integration depth, and support for features like Vertex AI’s “grounded responses” that depend on Google Search data.
• Cost transparency may challenge enterprise buyers, as billing structures tie external model usage to Oracle’s credit system.
• Organizations in highly regulated sectors may face questions about data custody and governance across different cloud domains.

Why this matters: The partnership signals a future where AI capabilities become interoperable building blocks rather than platform-locked services, giving enterprises more flexibility in their AI deployment strategies while reducing vendor lock-in risks.