Google Cloud has always been defined by choice, enterprise-grade governance, and market-leading price-performance. Key to the foundation of openness and choice is giving customers flexibility to run agentic workloads across their choice of models and infrastructure to achieve the right balance of cost, capability, and performance. Today, we are expanding that foundation by launching OpenAI models in Google Cloud’s model garden.
Google Cloud is now the only hyperscale cloud provider offering access to all three leading closed source LLMs, alongside more than 200 first-party, third-party, and open models on a unified enterprise AI platform.
The right model for every workload
Modern enterprise AI requires matching each workload to the right model rather than relying on a single model for every task. By adding OpenAI’s newest models to model garden, we are giving teams options across the full spectrum of enterprise workloads. For OpenAI models:
- GPT-6 Astra: Designed for demanding work across coding, computer use, professional tasks, and scientific research.
- GPT-6.1 Sol: Near-Astra intelligence at lower cost across agentic coding, computer use, and professional work.
- GPT-6 Luna: A fast, cost-efficient model for everyday work at scale.
Using the platform, customers can dynamically select and swap the optimal model for any use case based on performance, latency, and cost efficiency without architectural lock-in or separate vendor contracts. Developers gain the freedom to build with hundreds of choices in model garden. Because OpenAI models are transacted directly through Google Cloud Marketplace, all usage appears on a single Google Cloud invoice, draws down existing cloud commitments, and counts toward Flexible Savings Plans (FSP) across model providers.
Built-in data governance and enterprise security
Scaling generative AI should never require compromising on compliance or security. Built from the ground up for enterprise governance, the Gemini platform is trusted by leading global organizations today. We ensure that running any third-party or OpenAI workload meets the most rigorous enterprise standards:
- Strict data perimeters: Customer prompts, context, and outputs remain entirely within your designated data perimeter and are never used to train foundation models, with Zero Data Retention (ZDR) options available coming soon.
- Isolated access boundaries: OpenAI models run on dedicated Google Cloud infrastructure with Confidential Compute coming soon. All queries are routed through hardened, isolated gateways, ensuring data transit remains strictly within Google Cloud’s secure environment and third-party model providers have no unauthorized access to your cloud environment.
- Unified auditing and identity: Every agent and model interaction operates under an authenticated identity, giving IT administrators end-to-end visibility, VPC Service Controls protection, and unified audit logging across their entire enterprise footprint.
“Helping customers put AI to work across their enterprise content requires leading models backed by strong security and rigorous compliance standards,” said Yashodha Bhavnani, VP of AI Products at Box. “By using OpenAI models through Google Cloud, we will be able to give customers access to OpenAI’s frontier AI models alongside Google Cloud’s security and compliance capabilities, enabling them to get more value from their enterprise content. This is a step toward operating more efficiently as we bring AI to customers.”
Getting started
OpenAI’s GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna models are rolling out now in private preview to select enterprise customers in Google Cloud’s model garden, with more coming soon. Starting today, customers can build with these models through our APIs and connect their local Codex CLI and Desktop workflows directly to our Gemini platform for inference. Please use this form to express interest.
Coming soon, OpenAI models will be available in Google Cloud’s Gemini for business and Google Antigravity, providing enterprise customers and developers with model choice flexibility and the best model for each task.
