AlphaTON Capital Adds Deployment of 504 NVIDIA Blackwell B200 GPU Computers for AI Market Infrastructure

Core Insights - AlphaTON Capital Corp has signed a strategic $30 million lease agreement for AI compute infrastructure, adding 504 NVIDIA B200 chips to its capacity, which is expected to significantly scale its AI revenue with a 1.7x return multiple and 40% IRR [1][3] Group 1: Company Developments - The immediate deployment of the new GPUs is projected to generate a minimum of $1.2 million in monthly revenue starting March 2026, with potential revenue estimates reaching $1.45 million per month based on the hourly rental of the B200 chips [9][10] - AlphaTON's deployment of 504 NVIDIA B200 GPUs marks its third major deployment in under three months, demonstrating the company's operational capacity to secure and deploy AI infrastructure at scale [10][11] - The company has also signed a $46 million agreement to acquire a 576 NVIDIA B300 GPU half-cluster, scheduled for delivery in March 2026, indicating ongoing expansion efforts [10] Group 2: Market Dynamics - The demand for privacy-centric AI infrastructure is surging, with Big Tech projected to spend over $600 billion on AI capital expenditures in 2026, highlighting the sector's transformation into a systemic economic necessity [3][5] - Regulatory developments in the EU and stringent data localization requirements are driving demand for alternatives to Big Tech infrastructure, positioning North America as a potential leader in privacy-preserving AI solutions [5][11] - The market for AI compute technology is estimated to reach $7.2 trillion by 2030, driven by the needs of over 1 billion Telegram users [9][10] Group 3: Infrastructure and Sustainability - The new GPUs will be hosted in an energy-efficient data center in Canada, which offers advantages such as abundant clean hydroelectric power and a stable regulatory environment, contributing to lower operational costs and environmental sustainability [12][11] - AlphaTON's strategic shift towards capital-efficient growth through operational leasing structures allows for rapid scaling of its confidential compute capacity while maintaining balance sheet flexibility [11]