Foreign media commentary suggests that Decentralized Physical Infrastructure Networks (DePIN) are entering the traditional cloud services market through compute and storage sectors. While these networks are unlikely to replace AWS, Microsoft Azure, or Google Cloud in the short term, they are already gaining competitiveness in price-sensitive use cases such as AI training, 3D rendering, and batch processing.
DePIN focuses on aggregating underutilized resources.
The article states that traditional cloud platforms rely on self-built data centers, offering virtual machines, storage, and network services for rent. The fees paid by users cover not only hardware and operations but also real estate, depreciation, and platform profits.
In contrast, DePIN protocols function more like a decentralized computing marketplace. They aggregate idle GPU, server, and some consumer-grade hardware resources from enterprise data centers, then use smart contracts or automated scheduling mechanisms to handle node discovery, task assignment, and result verification.
Price and open access are the key selling points.
The article argues that DePIN's most direct advantage is cost. By prioritizing existing idle hardware instead of building large new data centers, these platforms can offer computing, storage, and rendering services at prices 50% to 80% lower than AWS. This is especially significant for AI startups requiring GPU clusters to train models.
- Computing and storage costs may be 50% to 80% lower than AWS.
- Developers can deploy applications on the open network.
- Tasks can be distributed and executed across multiple nodes worldwide.
There are still practical barriers to corporate adoption.
However, the article does not present DePIN as a mature alternative. AWS has established a comprehensive service ecosystem encompassing numerous tools such as object storage, serverless computing, and databases, whereas developer tools for DePIN-related products remain fragmented, and the use of cryptocurrency payments raises the barrier to entry.
The article suggests that a hybrid landscape is more likely to emerge in the future. Enterprise workloads with high compliance requirements and strong concurrency needs will remain on centralized cloud platforms in the short term, while cost-sensitive tasks such as AI model training, rendering, and batch processing may gradually shift to DePIN networks.