Compute Labs launches AI infrastructure tokenization product, with an expected annual yield of 30%
6월 19, 2025 10:48:19
ChainCatcher news, startup Compute Labs announced a collaboration with enterprise-level AI cloud service provider NexGen Cloud to launch a $1 million "Public Vault," which will tokenize industrial-grade GPU assets for investors. The expected annualized return in the first year could reach 30%, with profits paid in the stablecoin USDC.
According to the introduction, the project will split and tokenize high-performance NVIDIA H200 GPUs, allowing investors to participate in the profit distribution of enterprise-level AI computing infrastructure with costs starting from a few hundred dollars, without the need to directly manage hardware or bear the risks of technical operations. Each H200 GPU has a market price of about $30,000 and is primarily used for AI model training and inference.
Compute Labs stated that this is the first time real AI computing power profits are directly returned to investors in the form of stablecoins, aiming to break the monopoly of large cloud providers like AWS in the AI infrastructure field. Funds will be raised through NexGen Cloud's investment subsidiary InfraHub Compute and used to purchase GPU equipment, which will then be leased to data center operators with idle space. After deducting energy and hosting costs from the rent, the remaining will be returned to investors.
In terms of specific operations, the project adopts a token + NFT model for computing power ownership registration and profit distribution, with Compute Labs charging a unified fee of 10%, covering asset tokenization, management, and profit processing.
Compute Labs' Business Director Nikolay Filichkin stated that the target partners include small and medium-sized data centers, referred to as "mom-and-pop shops in the data center field." Additionally, the project has received investments from institutions such as Protocol Labs, OKX Ventures, CMS Holdings, and Amber Group.
NexGen Cloud co-founder and Chief Strategy Officer Youlian Tzanev stated that this model aims to drive the AI market from excessive speculation to rational pricing driven by supply and demand by assigning a clear, tradable value to each unit of GPU computing cycle.
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