Yotta ramps up AI push with additional $6 billion investment

Data centre and AI infrastructure provider Yotta Data Services is planning to invest an additional $6 billion to rapidly expand its artificial intelligence infrastructure, scaling up its deployment of Nvidia GPUs amid rising demand from domestic and international customers.

The company has increased its planned deployment of Nvidia Blackwell GPUs from 20,000 to 30,000. Built for accelerated AI training and inference workloads, the Blackwell chips will form the backbone of Yotta's expanding AI compute capacity. In addition, the company will deploy 8,000 Nvidia B200 GPUs over the next month and is evaluating the rollout of another 36,000-37,000 next-generation GB300 or Vera Rubin GPUs next year.

“The demand has been so high, not only from Indian customers but also global customers, that we are extending the 20,000 GPUs to 30,000 GPUs,” Yotta managing director and CEO Sunil Gupta told TOI.


According to Gupta, deploying the first 30,000 Blackwell GPUs will require an investment of around $3 billion. The proposed addition of 36,000 more GPUs could cost another $4 billion, while the separate deployment of 8,000 B200 GPUs involves an investment of nearly $600 million.

Yotta expects the first batch of 8,000 B200 GPUs to become operational within a month. The initial 20,000 Blackwell GPUs are scheduled to go live by September, followed by the remaining 10,000 units by November. The larger deployment of GB300 or Vera Rubin GPUs is planned for May next year.

The expansion underscores India's push to become a global AI compute hub as countries race to secure advanced computing infrastructure needed to develop and deploy AI models.

“India will have to become self-sufficient across the AI value chain. You cannot be dependent on a single company or a single country that can simply pull a kill switch,” Gupta said.

While Yotta is not developing foundation AI models, the company aims to provide the underlying infrastructure for sovereign AI initiatives as well as global AI firms. It currently operates a 2-gigawatt data centre campus in Mumbai and a 250-megawatt facility in Delhi, while also supporting several government workloads through National Informatics Centre data centres.