Nvidia seems to have caused SoftBank a lot of trouble. A sector-wide pullback hit Asian chip stocks Friday, led by a steep decline in SoftBank, after Nvidia’s sharp drop overnight defied its stronger-than-expected earnings and bullish outlook.
SoftBank plunged more than 10% in Tokyo as the Japanese tech conglomerate recently offloaded its Nvidia shares but still controls British semiconductor company Arm, which supplies Nvidia with chip architecture and designs.
In 2025, SoftBank deepened its technical collaboration with Nvidia even as it moved away from holding Nvidia as a financial asset. On the technology side, the two companies expanded their partnership around large-scale AI computing and telecommunications infrastructure. SoftBank deployed its AITRAS converged AI-RAN platform at Nvidia’s headquarters to support low-latency edge-AI experiments, making use of Nvidia’s GH200 Grace Hopper processors.
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SoftBank also announced the construction of one of the world’s largest AI supercomputing systems using Nvidia hardware: a DGX SuperPOD leveraging more than 4,000 Blackwell-generation GPUs and delivering over 13 exaflops of computing power. These initiatives reflect SoftBank’s strategy of embedding advanced AI and GPU capabilities into telecom networks, cloud environments, and edge-computing systems.
Billy Toh, regional head of retail research at CGS International Securities Singapore, said Nvidia was a victim of a combination of a Bitcoin selloff, the possibility of a delayed Fed rate cut and generally tighter financial conditions.
“Add in the ongoing talk of an AI bubble, which triggers a broader risk-off rotation, and naturally Nvidia becomes one of the first pressure points,” he told CNBC.
SoftBank’s push into large-scale AI computing represents a significant commitment to advancing technological capabilities. These initiatives may reflect SoftBank’s strategy of embedding advanced AI and GPU capabilities into telecom networks, cloud environments, and edge-computing systems.
The trajectory of AI and semiconductor investments will likely depend on technological advances, market adoption, and broader economic conditions, and SoftBank’s moves position it to be a central player in shaping next-generation computing solutions. The rapid pace of innovation also introduces challenges, including managing operational complexity and adapting to fluctuating market dynamics.
While these developments signal potential growth opportunities, they also underscore the need for careful execution and strategic planning to ensure the successful integration of advanced AI into commercial and research applications. The interplay between cutting-edge technology deployment and market reactions highlights the challenges faced by companies navigating both innovation and financial pressures in the rapidly evolving semiconductor and AI landscape.