This collaboration brings OpenAI’s frontier AI models and Codex agentic workflows to Google Cloud’s Model Garden, the companies announced Wednesday (Oct. 21).
The integration is designed to give customers “native access” to these models to power “complex agentic workflows” at scale, with Google Cloud’s data governance and “high-performance infrastructure” providing support.
“Google Cloud’s longstanding investment in machine learning and AI has made it a destination for AI workloads and the developers and data scientists building them,” OpenAI said.
“Bringing OpenAI models to its model garden gives these teams access to OpenAI’s frontier models within the environment where they already work, enabling enterprises to modernize their software development lifecycle, build agentic workflows, and change how people work.”
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The companies added that Google Cloud customers will be able to purchase OpenAI frontier models through model garden, with availability in Google Antigravity and the Gemini Agent, soon to come, “providing enterprise customers with model choice flexibility and the best model for each task.”
A report on the partnership from Reuters cites earlier comments from Google Cloud CEO Thomas Kurian that his company’s platform is an open one that welcomes any model popular with developers.
That report notes this collaboration is in keeping with a wider shift in the industry as hyperscalers are becoming the chief commercial channels for frontier AI labs. Cloud companies typically take a percentage from sales via their platforms.
Anthropic, an OpenAI competitor backed by Amazon and Google, has derived 47% of its 2025 revenue from those companies’ cloud platforms, according to its initial public offering (IPO) filing, Reuters added.
In other AI news, PYMNTS wrote Wednesday that while finance departments have moved quickly to put the technology to work, they have been much more hesitant in letting artificial intelligence act on its own.
Generative AI use for cash flow management surged from 16% in 2025 to 80% in 2026, according to PYMNTS Intelligence’s “Time to Cash: What Two Years of Data Say About Faster Cash and Rising Risk.” Agentic AI went the opposite direction, dipping from 6% to 5%, as detailed in the report, conducted in partnership with JPMorgan.
“The gap offers a measure of where finance automation stands,” PYMNTS wrote. “AI is becoming common in the systems that analyze cash and recommend what to do next, while autonomous execution remains rare.”
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