SoftBank swung back to profitability in its fiscal third quarter, reporting net income of 248.6 billion yuan — roughly $1.6 billion — for the three months ending December. These numbers, as reported by the Financial Times, represent a stark reversal from the 369 billion yuan (53.4 billion USD) loss the company posted in the same quarter last year.
This turnaround of the company’s fortunes was primarily driven by a $4.2 billion gain tied to its stake in OpenAI, which is part of a broader $17 billion in gains the company says it has recorded on the ChatGPT-maker in the financial year to date — strip out that contribution and the quarter would have looked very different.
Concentration by design
SoftBank has invested more than $34 billion in OpenAI and is understood to be in talks to commit another $30 billion in a funding round that could push its valuation to $750 billion. Following OpenAI’s restructuring last year, SoftBank holds roughly 11% of the company, compared with Microsoft’s near-27% stake.
To fund this, SoftBank has aggressively reshaped its balance sheet, exiting its entire position in Nvidia for $5.8 billion and selling $12.7 billion worth of T-Mobile shares. In doing so, Masayoshi Son effectively traded SoftBank’s exposure to public, liquid assets for a private AI platform and its associated infrastructure.
The company’s Vision Fund is reflective of why Son might have been keen to do this. Split into multiple parts, Vision Fund 1 recorded a $4.1 billion loss in the quarter, dragged down by declines in publicly-traded holdings like Coupang, which suffered a significant data breach. Meanwhile, Vision Fund 2, which includes OpenAI, generated a $6.6 billion gain, more than offsetting those losses.
The older portfolio, heavy with late-stage tech companies that are now exposed to public market volatility, is under serious pressure while the newer fund, anchored by OpenAI, is delivering gains at a scale large enough to dominate consolidated earnings. In effect, SoftBank’s quarterly performance is now increasingly tied to how OpenAI is valued.
Growing hardware strategy
(Image credit: Graphcore)
In addition to its heavy investment in OpenAI, SoftBank also retains a majority position in Arm, whose CPU architectures underpin much of the world’s mobile computing and an expanding share of the server silicon market. Arm is also known to be interested in manufacturing its own chips.
Over the past two years, SoftBank has also acquired Ampere, the Arm-based server CPU company founded by former Intel executive Renee James, and Graphcore, the UK AI accelerator startup that once claimed its Intelligence Processing Unit could be an alternative to GPUs in AI training and machine learning applications. SoftBank has said that these companies are now housed under a new unit — the AI Computing Segment — alongside Arm.
Anyone looking at this collection of assets can easily come to the conclusion that it resembles what appears to be a developing hardware strategy. Arm’s designs are already central to hyperscale data center applications, and Ampere’s server CPUs target cloud-native and AI workloads with high core counts and power efficiency. Graphcore, despite facing commercial headwinds, developed architectures purpose-built for machine learning. Overlay OpenAI’s model development needs on top of that, and you’ve got everything you need to support AI training and inference at scale. In fact, reports claim that Arm is developing a custom CPU to be used by OpenAI itself.
Cost of scaling AI
OpenAI’s valuation is tied to growth in both model capability and enterprise adoption — and both require infrastructure. Training frontier models demands clusters built around high-performance accelerators and high-bandwidth memory, and serving them at a global scale requires data centers with robust power delivery and cooling capacity.
SoftBank is playing a leading role in that buildout, with Son leading financing efforts for the $500 billion Stargate project — antitrust challenges ongoing — in the United States, which is aimed at scaling AI data centers and infrastructure in partnership with OpenAI, Oracle, and Abu Dhabi-backed DGX. It’s impossible to understate the capital intensity of such an undertaking, which involves land acquisitions, grid interconnections, power contracts, and vast quantities of silicon.
SoftBank’s shares have nearly doubled as a result over the past 12 months as investors seek exposure to OpenAI through the Japanese conglomerate. This has effectively turned the company into a publicly traded proxy for private AI valuation. However, the stock price has fallen 29% from its October peak, reflecting growing concerns surrounding the so-called AI bubble and intensifying competition from the likes of Google and Anthropic, and, naturally, the enormous, seemingly endless amounts of capital needed to sustain frontier model development.
As enterprise buyers grow increasingly sensitive to pricing and competition heats up from Anthropic’s Claude and Google’s Gemini models, which themselves are pushing performance boundaries, OpenAI’s ability to maintain competitive pricing will depend on continued technical leadership and efficient deployment of compute resources. That dynamic creates risk for SoftBank, given that a large portion of its recent profit derives directly from mark-to-market gains on OpenAI. If investor sentiment around AI reprices downward, those gains could be wiped out as quickly as they appeared.
SoftBank CFO Yoshimitsu Goto said that the group has made “over $40 billion of investments in the last nine months,” including commitments to OpenAI, while maintaining net debt at roughly 20% of the value of its equity holdings and a cash position of $24 billion. That, at least on paper, suggests some degree of financial discipline.
Luke James is a freelance writer and journalist. Although his background is in legal, he has a personal interest in all things tech, especially hardware and microelectronics, and anything regulatory.
