By Fenrir, CryptoCity
Mark Cuban: AI Chips Poised to Become the Next “Crypto” Asset Class
Billionaire investor Mark Cuban has once again made a bold prediction regarding the artificial intelligence industry. On August 16th, Cuban posted on X, stating, “Chips as an asset class will be the new crypto.” He posits that as the AI industry rapidly expands, high-end AI chips and the computational power they provide could gradually form a new and significant asset market.
Chips as an asset class will be the new crypto
— Mark Cuban (@mcuban) August 15, 2026
While Cuban did not elaborate on the specific types of chips he was referring to or propose concrete financial products or investment plans, his statement is widely interpreted to concern high-end GPUs like Nvidia H100 and B200. These powerful units, essential for AI training and inference, have become critical resources for the expansion of large language models, cloud computing, and data centers.
The core logic behind this perspective stems from the confluence of scarcity and escalating computational demand. With the explosive growth of generative AI, enterprises require significantly more high-performance computing capabilities. Consequently, the supply of advanced GPUs and data center capacity has emerged as a crucial competitive battleground within the AI sector. Nvidia’s recent quarterly data center revenue, which surged to $75.2 billion with a 92% year-over-year increase, vividly underscores the immense market demand for AI computing infrastructure.
GPUs Emerge as Collateral: Wall Street Financializes Compute Power
Cuban’s foresight is already finding validation in nascent developments within the financial markets. CoreWeave, an AI cloud computing company, has increasingly leveraged its GPU assets to secure financing. In August of this year, CoreWeave finalized a substantial $2.6 billion deferred draw term loan specifically for high-performance computing infrastructure. This financing, with a term of approximately five years, remarkably extends beyond the duration of some client contracts underpinning the loan.
Earlier in May, CoreWeave also secured another $3.1 billion in publicly syndicated financing, explicitly labeling AI infrastructure financing as an “emerging asset class.” These transactions signify that high-end GPUs are beginning to exhibit characteristics of financial assets, with financial institutions willing to assess their future cash-generating potential and provide capital based on these valuations.
Further evolution is evident in the derivatives market. CME Group is slated to launch futures products on October 5th, based on the rental prices of Nvidia H100 and B200 GPUs. This groundbreaking move will enable market participants to hedge against future computing costs and engage in speculative trading. AI developers and cloud service providers can thus pre-emptively lock in portions of their GPU rental expenses, pushing the compute power market towards standardized commodity trading.
From Chip Acquisition to Compute Monetization: AI Infrastructure as an Asset
The distinctive value proposition of AI chips lies in their ability to directly generate cash flow by renting out their computational capacity. Companies acquire GPUs, deploy them within data centers, and then offer this compute power to AI model developers, cloud service providers, and other enterprises. Revenue is subsequently generated through long-term contracts or usage-based billing models.
This paradigm shift transforms GPUs from mere corporate hardware into infrastructure assets capable of quantifiable income generation. As financial institutions increasingly accept GPUs as collateral for financing and exchanges begin to establish futures markets for compute power, factors such as chip prices, rental rates, utilization metrics, and projected future cash flows are becoming integral to financial market valuation models.
Cuban’s analogy of “the new crypto” more accurately refers to AI chips forming a new asset class characterized by scarcity, market-driven pricing, collateral value, and tradable derivatives. As the demand for compute power intensifies, the objects of market trading are likely to expand beyond physical chips to encompass the very computational capacity these chips deliver.
Fundamental Differences Remain, Compute Assetization Still in Early Stages
Despite the intriguing parallels, significant differences persist between AI chips and cryptocurrencies. Bitcoin ($BTC), for instance, boasts verifiable ownership and transferability via a transparent blockchain, trades globally 24/7, and its supply rules are immutably pre-programmed by its protocol. In contrast, GPUs are physical hardware requiring secure data center environments and are subject to depreciation, wear and tear, substantial energy costs, and rapid technological obsolescence.
Bitcoin proponent Pierre Rochard has also challenged Cuban’s analogy, pointing out that chip production lacks Bitcoin’s built-in halving events and difficulty adjustment mechanisms. When market demand surges, semiconductor companies can scale up production. Furthermore, the introduction of newer generation chips can rapidly diminish the economic value of older GPUs.
Currently, the market is still some distance from AI chips forming a complete and independent asset class, and Cuban has not offered a specific timeline or financial framework. Nevertheless, the emergence of GPU-backed financing, a burgeoning compute rental market, and related futures products clearly indicate that AI infrastructure is progressively acquiring the attributes necessary for financialization.
Should compute power achieve further standardization, pricing, collateralization, and trading mechanisms in the future, investors’ portfolios might expand beyond shares in chip companies like Nvidia to include the GPUs themselves and the ongoing computational capacity they provide. Cuban’s prediction thus highlights a crucial direction for the next phase of the AI industry, where compute power is increasingly recognized as a scarce resource fiercely contested by enterprises, and its financial value begins to garner significant market attention.
(The above content is an authorized excerpt and reprint from our partner CryptoCity.)
Disclaimer: This article is for market information purposes only. All content and opinions are for reference only and do not constitute investment advice. They do not represent the views and positions of BlockTempo. Investors should make their own decisions and trades. The author and BlockTempo will not bear any responsibility for direct or indirect losses incurred by investors’ transactions.
