The reported move could strengthen Google’s chip business and give OpenAI another option beyond Nvidia as demand for AI computing capacity continues to rise.
OpenAI is planning to purchase artificial intelligence chips from Google, according to a report by The Information, signalling a potential expansion of the companies’ commercial relationship despite their competition in the AI market.
The report, citing a person familiar with the matter, did not disclose the financial terms, volume of chips or expected timeline for the purchase. Neither company provided further details on the reported plan, according to Reuters.
The potential purchase comes as technology companies race to secure the computing infrastructure required to develop, train and operate increasingly sophisticated AI models. For OpenAI, which relies heavily on Nvidia’s graphics processing units (GPUs), adding Google’s chips could provide another source of computing capacity and reduce its dependence on a single dominant supplier.
Google’s TPUs emerge as an alternative to Nvidia
Google’s Tensor Processing Units (TPUs) are specialised chips developed to accelerate machine-learning workloads. While Nvidia’s GPUs remain central to the AI computing market, TPUs have gained traction as an alternative for companies seeking different cost and performance options.
Google has made its TPUs available to external customers through its cloud infrastructure and has expanded efforts to supply them beyond its own data centres. Companies including Anthropic and Apple have used Google’s chips for AI-related workloads, according to Reuters.
OpenAI had already begun renting Google’s AI chips through Google Cloud in 2025, according to Reuters. A direct purchase, if completed, would represent a further step in its use of hardware developed by a company that also competes with it through products such as Gemini.
OpenAI looks beyond a single chip supplier
OpenAI remains a major Nvidia customer, using GPUs to train its models and run inference, the process through which trained models generate responses to user requests.
However, the company’s reported interest in TPUs reflects a broader effort across the AI industry to secure sufficient computing capacity while managing costs and supply-chain dependencies. Demand for processing power has risen alongside the expansion of generative AI products, enterprise adoption and increasingly complex models.
The Information has also reported that OpenAI was seeking engineers to optimise its advanced models for Google’s TPUs. Such work would be important for ensuring that its models can run efficiently on a different hardware architecture, rather than relying solely on chips and systems already integrated into its infrastructure.
OpenAI is also developing custom AI accelerators with Broadcom. The companies announced a collaboration in October 2025 to develop and deploy custom AI accelerator and networking systems, with deployments targeted to begin in the second half of 2026. Together, these developments point towards a more diversified computing strategy, although the reported Google purchase and the extent of any future deployment remain unconfirmed.
A commercial opportunity for Google
A purchase by OpenAI would be a significant development for Google’s chip business. It would demonstrate that demand for TPUs can extend to one of the largest developers of competing AI models, potentially strengthening Google’s position in a market long dominated by Nvidia.
Google’s opportunity extends beyond selling chips. Its cloud business can also benefit when customers use its infrastructure to access AI computing resources. The company has been expanding external access to TPUs as competition intensifies among cloud providers and semiconductor suppliers.
The development also highlights how commercial relationships in the AI industry can cross competitive boundaries. OpenAI and Google compete for users, developers and enterprise AI spending, yet their infrastructure businesses can still find opportunities to work together.
What it means for the AI infrastructure market
The reported plan underscores a shift in the AI industry: competition is no longer limited to models and applications. Access to chips, data centres, energy and cloud infrastructure is becoming an equally important part of the race.
For OpenAI, additional hardware options could improve flexibility as it scales its services. For Google, a deal could validate its efforts to build a larger external market for its in-house chips. For Nvidia, the development adds to the competitive pressure as major AI companies explore alternatives, develop custom silicon and negotiate access to computing resources.
The key question is whether OpenAI’s reported interest translates into a completed purchase and meaningful deployment at scale. Until further details emerge, the development signals a possible diversification of AI infrastructure rather than a confirmed shift away from Nvidia.
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