What Is DePIN? - Decentralized Physical Infrastructure Networks

Much of the digital infrastructure people rely on today, including cloud computing, data storage, payments, and communication networks, is operated by a small number of providers. As more organizations depend on the same infrastructure, security incidents and operational failures can have far-reaching consequences. This became evident during the 2024 Snowflake customer data theft campaign, where attackers used stolen credentials to access around 165 customer environments and expose more than 500 million user records.

Although Snowflake itself was not compromised, the incident highlighted the risks of infrastructure concentration and how failures at a common infrastructure layer can affect hundreds of organizations. DePIN (Decentralized Physical Infrastructure Networks) aims to reduce this concentration by using blockchain and token incentives to coordinate distributed providers of storage, computing, connectivity, sensors, and energy. Instead of relying on a single company to build and operate infrastructure, DePIN distributes these responsibilities across independent participants.

What is Depin

DePIN refers to infrastructure networks that use blockchain technology to coordinate user-provided resources such as storage, computing power, bandwidth, and wireless connectivity. Instead of relying on a single company to own and operate infrastructure, DePIN enables individuals and organizations to contribute unused resources to a shared network in exchange for token rewards.

The growing interest in DePIN is driven by several structural trends. As AI and blockchain applications become more resource-intensive, demand for computing, storage, and bandwidth continues to increase, while infrastructure costs remain concentrated among a handful of cloud providers such as AWS and Google Cloud. At the same time, reliance on centralized infrastructure creates systemic risks. The AWS outage in the US-EAST-1 region in October 2025 demonstrated how a failure at a single provider could disrupt services across platforms including Reddit, Zoom, Coinbase, and Snapchat.

How DePIN works
DePIN uses blockchain technology and economic incentives to coordinate a network of individuals and organizations that provide physical infrastructure. Depending on the project, contributed resources may include GPUs, storage capacity, bandwidth, wireless coverage, sensor data, or energy. During the initial stage, a network typically issues tokens to encourage participants to purchase equipment, contribute resources, and expand coverage. This mechanism helps the project address the initial supply shortage without having to invest in all the required hardware itself, as a traditional infrastructure company would.

Once the available supply reaches sufficient scale and quality, the project must attract paying customers to use its services. A portion of the resulting revenue may be distributed to resource providers, used to buy or burn tokens, or allocated to protocol operations. The flywheel can continue only when paying demand grows enough to reduce the network’s dependence on newly issued tokens.

Helium is a representative example. The project uses token rewards to encourage community members to deploy hotspots and provide wireless coverage. Businesses and developers then use Data Credits to pay for data transmission through the network. This model shows that DePIN generally requires two separate groups of participants: infrastructure providers and customers who pay to use that infrastructure. From a technical perspective, a DePIN network generally includes the following components.

• Physical infrastructure includes hotspots, routers, GPUs, storage servers, sensors, weather stations, and energy equipment.

• The connectivity and data collection layer transfers information from devices to the processing system.

• The verification layer checks device identities, locations, service quality, and completed workloads.

• Blockchain networks and smart contracts record activity, distribute rewards, and process payments between participants.

• Marketplaces and applications allow customers to purchase, access, and use resources provided by the network.

• Economic and governance mechanisms determine service prices, rewards, penalties, and participation standards.

Blockchain technology makes data and transactions publicly verifiable, but it cannot independently guarantee that information from the physical world is accurate. DePIN security therefore also depends on device verification, fraud prevention, cross-checking mechanisms, and the way rewards are linked to useful work. DePIN models may also use device registration, multiple sensor sources, and reward and penalty mechanisms to limit fraudulent activity.

History of DePIN development

Formation of the model

Decentralized infrastructure networks appeared before DePIN became a widely used market narrative. Helium began building a community-operated wireless network in 2019, while Filecoin launched its decentralized storage network in 2020. These projects helped establish a model that uses tokens to encourage users to contribute devices, storage capacity, and other physical resources to blockchain-coordinated networks. In November 2021, IoTeX introduced MachineFi, a concept that combined machines, device data, and blockchain technology to create economic value for device owners and operators. MachineFi represented one of the early interpretations of the model that later became widely known as DePIN. During 2022, the market used several different terms, including TIPIN, Proof of Physical Work, and EdgeFi. In November 2022, Messari organized a poll to select a common name for the sector. DePIN received the largest share of votes and gradually became the most widely used term.

Expansion from 2023 to 2024

From 2023, DePIN developed into a more clearly defined group of projects covering wireless networks, storage, computing, sensors, mapping equipment, and energy infrastructure. According to Messari, more than 650 projects were classified under the DePIN narrative in 2023, while the total market capitalization of circulating DePIN tokens exceeded $20B. In the computing sector, io.net was one of the projects that expanded rapidly during this period. According to the project’s 2024 State of the Network report, the network provided more than 1M computing hours, processed nearly 2M on-chain transactions, and assembled tens of thousands of GPUs that could participate in computing clusters across more than 138 countries. io.net also reported signing 56 agreements with customers and partners. These figures demonstrate the ability of DePIN networks to aggregate distributed GPU supply, although the report did not provide sufficient information about the percentage of GPUs that were actually rented or the revenue generated by each customer group.

Helium provides a clearer example of the shift from infrastructure deployment to service demand. By mid-May 2024, Helium Mobile was approaching 100K subscribers. Between the beginning of the year and May 16, nearly 160K HNT was burned to purchase Data Credits, representing more than $1.47M in network usage costs. Helium’s IoT network also had more than 100 organizations operating applications or purchasing network traffic. These figures indicate that Helium’s value had started to depend more heavily on subscriptions, transmitted data, and service fees rather than only on the number of deployed hotspots.

In the storage sector, Filecoin also recorded stronger network usage during 2024. The project’s Q1 report showed that active storage deals increased by 9% quarter over quarter, capacity utilization reached 23%, and more than 2K customers stored data on the network. Of these customers, 508 stored large datasets. By Q2, capacity utilization had exceeded 26%, even as the total available storage capacity declined. This trend was more significant than the total storage capacity alone because it indicated that customers were making greater use of the infrastructure already deployed.

This expansion was supported by several factors.

• Token rewards attracted underused resources from individuals and organizations into DePIN networks. This created a broader pool of resources that could support different computing requirements.

• User demand for the computing capacity, data, and hardware services provided by DePIN projects also became more visible. One factor attracting customers was the ability of these services to offer lower and more competitive prices than traditional providers.

• The development of faster and lower-cost blockchain infrastructure also supported the sector. Solana quickly became one of the most prominent networks for DePIN projects. Helium migrated to Solana, followed by Render Network and several other computing and bandwidth projects that also developed within the Solana ecosystem.

• Venture capital funding continued to increase during 2024. According to Messari, DePIN projects raised more than $350M, reflecting part of the confidence that crypto-focused venture capital firms had in the sector.
  

Model validation stage

After the initial expansion of supply, DePIN’s focus shifted toward generating real demand. A network may deploy thousands of devices through token rewards, but that scale creates limited value if most resources remain unused or the number of paying customers does not increase accordingly. DePIN development should therefore not be evaluated only through market capitalization, connected devices, or distributed tokens. More relevant indicators include

• The percentage of resources that are actually used

• The number of paying customers

• Service revenue

• Device activity levels

• The percentage of rewards funded by revenue rather than newly issued tokens

Filecoin shows how large infrastructure capacity does not necessarily indicate a sustainable economic model. According to Token Terminal, between May and July 2026, the protocol generated approximately $89K to $116K in monthly revenue. During the same period, token incentive expenses for participants who supplied and secured the network ranged from $717K to $2M per month. This gap kept Filecoin’s earnings negative, ranging from approximately negative $605K in July to negative $1.9M in May. This does not mean Filecoin paid the full amount in cash. Most of the expense came from newly issued FIL, meaning that the economic burden primarily appeared through supply dilution. However, the data still indicates that revenue generated by network usage was not sufficient to offset the tokens used to maintain infrastructure supply.

Filecoin reflects a common challenge across DePIN. Token incentives can quickly attract devices, storage capacity, and resource providers, but the model moves closer to sustainability only when customer revenue grows faster than incentive expenses. In addition to total storage capacity, users should therefore monitor actual utilization, revenue per unit of resources, and the network’s dependence on newly issued FIL.

Service quality is another important part of the validation process. A distributed network may provide resources at a lower cost, but it must still meet requirements related to uptime, latency, processing speed, data accuracy, and customer support. If service quality varies significantly between providers, the cost advantage may not be sufficient to retain customers.

• The model becomes sustainable only when the interests of all three participant groups are balanced.

• Resource providers need sufficient income to cover hardware, electricity, maintenance, and depreciation costs.

• Customers need services that can compete with traditional infrastructure in both price and quality.

The project coordinating the network must generate enough revenue to maintain operations without depending excessively on token issuance. After the initial user acquisition period, the main question is whether the network can retain supply as rewards decline while continuing to attract demand from businesses and customers outside the crypto market. This separates a network with product-market fit from a growth model driven primarily by token subsidies.

DePIN ecosystem

Based on the type of resources they provide, DePIN projects can be divided into two primary groups, Physical Resource Networks and Digital Resource Networks. Both rely on physical hardware, but they differ in how dependent their services are on geographical location. Physical Resource Networks provide services tied to specific locations. Digital Resource Networks convert hardware capacity into digital resources that customers can access through the internet.

Physical Resource Networks

Physical Resource Networks, or PRNs, use devices deployed at specific locations to provide services in the physical world. The value of each device depends on its location, operating range, network density, and local demand.

For example, a hotspot providing connectivity in Hanoi cannot directly replace one located in New York City. Similarly, mapping cameras must travel along the specific roads where data is needed, while positioning stations must be installed in areas that do not already have sufficient coverage. PRN participants typically need to purchase or install specialized equipment, maintain network connectivity, and ensure that their devices operate consistently. Rewards may be calculated based on coverage, location, uptime, data quality, or the amount of service actually delivered.

Some notable projects include

• Helium: Community members deploy hotspots to provide LoRaWAN connectivity for IoT devices and Wi-Fi infrastructure for cellular offload. Hotspot operators receive HNT for providing coverage and processing traffic, while network users pay with Data Credits. Because the service depends on coverage, hotspot location directly affects the value generated by each device.

• Hivemapper: Participants use supported dashboard cameras to collect street-level imagery. AI systems then process the images to build and update maps. The network also encourages users to revisit previously mapped areas to maintain data freshness rather than mapping each road only once.

• GEODNET: Users install fixed GNSS stations to collect satellite data and provide RTK correction signals. This data can help drones, robots, autonomous vehicles, and surveying equipment determine their positions more accurately. Each station adds coverage only to its surrounding area, making deployment location an important component of the network’s value.

PRNs connect blockchain networks with services that can be observed in the physical world. However, they often expand more slowly because providers must purchase equipment, select suitable locations, complete installation, and perform long-term maintenance. A network may have many devices but still create excess supply if they are concentrated in areas with limited demand.

Digital Resource Networks

Digital Resource Networks, or DRNs, aggregate digital resources produced by GPUs, CPUs, servers, storage devices, and networking equipment. Customers can rent and use these resources through the internet without owning the underlying hardware. Unlike PRNs, the value of DRNs depends less on the exact location of each device. A GPU or storage unit in one country can replace equivalent capacity in another if it meets the required standards for performance, latency, security, and accessibility. Providers can connect existing hardware to the network and earn additional income from unused capacity. The project acts as an intermediary that verifies hardware specifications, distributes workloads, monitors service quality, and processes payments between providers and customers.

Some notable projects include

• Filecoin: The network connects customers who need data storage with storage providers that operate storage devices and server infrastructure. Filecoin uses economic mechanisms and cryptographic proofs to verify that data remains stored according to the agreed terms. Providers may receive payments from customers and FIL rewards from the network.

• Render Network: GPU owners contribute unused processing capacity to artists, studios, and creators that need rendering services. Node operators register their GPUs with the network, receive workloads that match their hardware specifications, and are paid after completing the assigned tasks. The network is also expanding its support for computing and AI workloads.

• Akash Network: The project provides a decentralized marketplace for GPU and cloud computing resources. Customers can deploy AI workloads by renting compute from independent providers, while providers monetize their unused GPU capacity. Akash is also one of the GPU compute providers available on OpenRouter.

• Phala Network: Phala provides decentralized GPU computing for AI inference and agent workloads. Developers can access GPU resources through the network, while node operators earn rewards by contributing computing power. Phala is also available as a GPU compute provider on OpenRouter.

DRNs may expand faster because they can use existing hardware and distribute services through the internet. However, the available supply is often inconsistent. GPUs, servers, and network connections can vary significantly in performance, uptime, and reliability, requiring projects to implement strict benchmarking, monitoring, and workload verification systems. The main difference between the two groups is not whether they use physical hardware. PRNs provide services tied to specific locations, while DRNs convert hardware capacity into digital resources that can be distributed to customers through the internet.

Opportunities and challenges of DePIN

Opportunities

DePIN may create a more affordable infrastructure layer by using underutilized GPUs, storage devices, and bandwidth. For example, Akash currently lists H100 GPUs at approximately $2.09 to $2.73 per hour and promotes some available capacity from $1.33 per hour, compared with approximately $3.93 on AWS. This price difference is only a general reference because configurations, regions, memory capacity, technical support, and rental structures may differ between providers.

This advantage makes DePIN suitable for AI startups, independent developers, and workloads that can use flexible server locations. DePIN is unlikely to replace AWS or Google Cloud completely, but it may provide additional capacity when GPUs on major cloud platforms are expensive, scarce, or require long-term commitments.

Challenges

Despite its potential, DePIN still faces several challenges before it can compete with traditional cloud providers at scale. Unlike AWS or Google Cloud, which own and manage their data center infrastructure, DePIN networks rely on hardware contributed by independent participants. As a result, hardware quality, internet connectivity, maintenance standards, and geographic distribution can vary significantly, making it more difficult to guarantee consistent performance and uptime. Another challenge is the economic model. Most DePIN networks depend on token incentives to attract hardware providers, but the long-term sustainability of these incentives remains largely unproven. If token rewards decline or demand is insufficient, providers may disconnect their hardware, reducing the network's available capacity. Scalability is also a major concern. While DePIN networks can aggregate thousands of distributed devices, coordinating them into a reliable, high-performance compute cluster is technically complex. This is particularly important for AI workloads, which often require low latency, predictable performance, and tightly synchronized GPU resources. Finally, maintaining a decentralized infrastructure is more difficult than operating centralized data centers. Hardware failures, software updates, security issues, and node availability must all be managed across thousands of independently operated devices, increasing operational complexity for the network.

Conclusion

DePIN represents one of blockchain's most ambitious attempts to connect digital incentives with real-world infrastructure. By allowing anyone to contribute computing power, storage, bandwidth, or other physical resources, it offers an alternative model to the centralized infrastructure dominated by major cloud providers. However, decentralization alone is not enough to guarantee success. DePIN networks still face significant challenges, including maintaining consistent uptime, coordinating distributed resources at scale, sustaining their economic incentive models, and delivering enterprise-grade reliability. These limitations are particularly important for compute-intensive applications such as AI, where performance, latency, and availability are critical. As the ecosystem matures, the success of a DePIN project will depend less on its token price or the number of participating nodes and more on its ability to attract real customers, generate sustainable revenue, and provide reliable services that can compete with traditional infrastructure providers. When evaluating a DePIN project, users should therefore focus on resource utilization, service quality, actual demand, and the long-term sustainability of its incentive model rather than market capitalization or node counts alone.