Nvidia Adds Another $1.5B Investment in SB Energy, Bringing Total Pre-IPO Bet to $3B
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Nvidia bought another $1.5 billion in SB Energy shares at a 10% discount to IPO price, lifting its total bet to $3 billion — the world's most valuable chipmaker is locking in AI's power gateway before the listing window opens.
What exactly did Nvidia buy?
Nvidia subscribed to new Class N non-voting shares in SB Energy via a private placement worth $1.5 billion.
The price was 90% of the IPO offer price. This means → Nvidia secured a 10% discount versus public-market investors, trading away voting rights for a cheaper entry.
Combined with a prior $1.5 billion tranche, Nvidia's total position in SB Energy now stands at $3 billion.
What is SB Energy?
SB Energy is a SoftBank-owned data-center operator with 8.8 gigawatts of capacity under construction or contract.
In plain terms = 8.8 GW is roughly the output of eight large nuclear plants, all dedicated to powering and cooling AI servers.
Its projects sit mainly in Texas and Ohio, riding directly on the ongoing build-out of AI compute infrastructure.
Why is Nvidia piling in before the IPO?
This reflects Nvidia's systematic push into the upstream and downstream AI supply chain — not just selling chips, but locking in the power and physical space those chips need to run.
Buying at a 10% pre-IPO discount, this means → Nvidia is positioning itself as SB Energy's anchor investor, securing a bargain while signaling confidence to the market.
Notably, OpenAI is also a shareholder in SB Energy, and OpenAI itself is preparing an IPO — several AI giants are cross-holding stakes at the data-center layer.
What does this mean for the market?
SB Energy's IPO pricing will serve as a key benchmark for how the market values data-center infrastructure assets.
In plain terms = however much this company fetches at listing directly shows the premium Wall Street is willing to pay for the business of "powering AI."
The world's most valuable company placing a direct bet here, this reflects a broader shift — the bottleneck in the AI race is moving from chips to power and physical infrastructure.
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