Meta Considers Google TPUs as an Alternative to NVIDIA Chips

Meta is considering deploying Google’s Tensor Processing Units (TPUs) in its data centres from 2027, a move that could challenge NVIDIA’s longstanding dominance in AI hardware, according to The Information.

Meta is reportedly in talks to spend billions on TPUs, exploring both long-term deployment and the possibility of renting Google’s chips through Google Cloud as early as next year, reported The Information. 

The discussions come as major AI developers look to diversify suppliers amid soaring demand and concerns over dependence on NVIDIA GPUs, which are the current industry standard for training and running large AI models.

Interestingly, Google’s latest model Gemini 3, was also trained on TPUs. 

Alphabet shares rose as much as 2.7% in late trading following the report, while NVIDIA slipped by a similar margin, reflecting investor expectations of a potential shift in market dynamics.

If finalised, the Meta–Google arrangement would bolster TPUs as a credible alternative in high-performance AI computing. Google has already signed a separate agreement to provide up to one million TPUs to Anthropic. 

With Meta’s capital expenditure projected to exceed $100 billion in 2026, Bloomberg analysts estimate the company could spend $40–$50 billion next year on inferencing-chip capacity alone, potentially accelerating demand for Google Cloud services.

TPUs, designed more than a decade ago specifically for AI workloads, have gained traction as companies evaluate customised, power-efficient alternatives to traditional GPUs. While NVIDIA still commands the vast majority of the AI chip market and AMD remains a distant second, TPUs are emerging as a strong contender, especially as companies seek to mitigate reliance on a single dominant supplier.

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