DePIN assets represent non-speculative use cases for cryptocurrency adoption in the real world.

Written by: Will Ogden Moore, Grayscale

Compiled by: Tao Zhu, Golden Finance

Abstract

• Compared to traditional alternatives, blockchain technology can more effectively direct capital to critical physical infrastructure projects. These projects are known as Decentralized Physical Infrastructure Networks (DePIN), which include wireless connectivity platforms, AI-related resources (such as computing and data), and other applications.
• DePIN assets represent non-speculative use cases for cryptocurrency adoption in the real world, as networks utilize tokens as economic incentives to facilitate the sharing of these resources.
• Solana is currently the leading blockchain for DePIN, as it hosts some of the top-ranked DePIN by market capitalization, usage, and adoption, including Helium, Render, and Grass. Solana has become the preferred DePIN blockchain due to its speed, cost-effectiveness, and reliability. Grayscale offers Solana investment opportunities to qualified accredited investors through Grayscale Solana Trust.
• AI-related DePIN accounts for a dominant share of this theme by market capitalization (48%). These assets include functionalities such as decentralized AI model training, computing, data scraping, and storage. Grayscale Research is particularly interested in emerging decentralized model training use cases. The Grayscale AI Fund offers many AI-related DePIN projects to qualified accredited investors, including Bittensor (TAO).

In January of this year, President Trump and First Lady Melania Trump launched a memecoin on the Solana chain, bringing Solana into the mainstream media spotlight. While Solana is currently the dominant blockchain for memecoin trading, it is also a key non-speculative use case in cryptocurrency: Decentralized Physical Infrastructure Networks (DePIN).

What is DePIN?

DePIN represents a unique emerging field: connecting blockchain with the real world. These physical systems include hotspot devices, wireless routers, physical Internet of Things (IoT) sensors, car dash cams, and GPUs, which meet demands for internet connectivity and computing resources. These devices provide value through the network in exchange for cryptocurrency token rewards. Unlike traditional models that rely on companies like telecom providers and data centers, DePIN is decentralized, distributing ownership and management among various independent participants. Within the Grayscale Research framework, DePIN assets belong to the utility and service crypto sector, functioning as application layer protocols running on smart contract blockchains like Ethereum or Solana.

DePIN Investment Outlook

As DePIN distributes physical nodes among different participants, it helps eliminate single points of failure and enhances the resilience, efficiency, and sustainability of infrastructure. In this way, DePIN can foster innovation, promote equity, and provide greater flexibility while reducing operational costs. In summary, DePIN may have several key advantages over traditional centralized models:

• Eliminates the need for centralized intermediaries
• Reduces single points of failure and improves responsiveness to rapid demand
• Eliminates management costs, sometimes lowering prices for consumers
• Coordinates incentive mechanisms among all participants, including resource providers and consumers

Due to these advantages, DePIN is particularly relevant to industries with high capital requirements, high barriers to entry, monopolistic dynamics, and underutilization of resources. The DePIN model is especially relevant in areas such as internet connectivity, data storage, and computing hardware for AI development. These industries are worth trillions of dollars and include some of the largest companies in the world, from AT&T to Amazon (AWS) and Nvidia.

Therefore, we believe the opportunities are significant; if DePIN captures even a small portion of these markets, the potential impact could be enormous. Grayscale Research believes this outcome is feasible because 1) DePIN offers a more efficient business model than traditional alternatives, and 2) there are already examples of DePIN successfully utilizing crypto incentives to scale network supply.

Today, we believe Solana is the best way to gain exposure to this early and growing thematic investment opportunity, as the preferred blockchain for DePIN (which will be detailed later). However, we also believe several DePIN projects have already demonstrated impressive levels of adoption and are emerging as potential category winners.

The Current State of DePIN

The use cases for DePIN assets are diverse, including wireless connectivity and IoT (Helium), geospatial data collection (Hivemapper), decentralized video streaming (Render), and AI-related use cases such as computing networks (Akash). Today, AI-related DePIN projects dominate by market capitalization (Figure 1). In the following sections, we will highlight some of these emerging use cases and projects.

Figure 1: AI-related DePIN projects dominate by market capitalization

Helium — Wireless Connectivity and IoT

Headquartered on Solana, Helium is one of the early pioneers of DePIN and a typical example of real-world cryptocurrency usage. Helium enables individuals to monetize their unused network capacity in exchange for token rewards (HNT), creating a decentralized hotspot network. Users access internet connectivity through this hotspot network at a significantly lower cost than traditional alternatives. Helium currently has over 129,000 mobile users, offering an unlimited data plan for $30 per month—far below the average of $144 per month in the U.S. Notably, Helium recently announced its free mobile plan, which has limited data, SMS, and call time.

Helium has also partnered with telecom providers like T-Mobile. Through this partnership, T-Mobile users can seamlessly access Helium's wireless connectivity in high-traffic areas, reducing congestion and costs. T-Mobile pays Helium's network based on usage, creating a deflationary effect on the supply of HNT. Thanks in large part to corporate efforts, Helium has provided wireless internet access to approximately 450,000 people and is expected to see an increase in overall network usage in the second half of 2025 (Chart 2).

In addition to mobile connectivity, Helium also supports IoT devices, allowing sensors to transmit data through its decentralized network at a lower cost than traditional Wi-Fi solutions. Similar DePIN projects focused on IoT solutions include Geodnet, Hivemapper, and NATIX, which use IoT sensors in cars or homes to collect real-time geospatial data. This data is highly valuable for today's navigation services and can improve the accuracy of AI systems such as autonomous vehicles and robotics. Notably, Geodnet has seen astonishing growth in annual network fee revenue, reaching $3 million in January 2025 (an increase of approximately 518% year-over-year).

Grayscale Research believes that if Helium can 1) continue to expand its usage and geographic coverage in its current partnerships with T-Mobile and Telefonica, and 2) gain broader consumer recognition through its new free mobile plan, its opportunities could be significant.

Figure 2: Helium network usage is expected to increase by the second half of 2024

Data Scraping — Grass

DePIN has significant overlap with AI use cases; one example is data collection. Large language models (LLMs) require vast amounts of high-quality data. Existing AI services like OpenAI and Gemini continuously access real-time and multimodal data through Bing and Google, respectively, giving them a significant advantage over competitors. Grass aims to create a level playing field by enabling a new data collection model driven by token incentives.

Through a simple desktop application, Grass allows anyone to share their unused internet bandwidth in exchange for GRASS tokens. This bandwidth is used to scrape online data, which is then sold to AI companies and developers for model training. As a result, individuals on the Grass network can monetize their bandwidth, while AI companies can access data that would otherwise be trapped in silos.

Grass is one of the success stories of DePIN, utilizing token incentives to guide supply and expanding its contributor base to 2.5 million nodes across 190 countries—more than any other DePIN project. With such a large amount of bandwidth, Grass has scraped 20% of YouTube's data, totaling over 7,000 TB of data. The Grass network currently provides data to AI labs such as Laion and Ontocord, and there may be significant upside potential if it can collaborate with some larger AI labs.

Competitors in this space include Masa, which offers similar decentralized data scraping services for the Bittensor ecosystem.

Chart 3: Total amount of data scraped by Grass since last November

AI Model Training — Prime Intellect and Others

Once AI companies obtain high-quality data, they can use it to train LLMs (large language models). One of the earliest use cases for DePIN (but still potentially one of the most promising) is decentralized training.

AI model training requires immense computational power, typically concentrated in centralized data centers. DePIN is changing this landscape. By distributing workloads across a global GPU network, these projects unlock decentralized training. In November of last year, Prime Intellect successfully trained a 10 billion parameter language model on one trillion tokens across five countries and three continents. Prime Intellect achieved this using their DiLoCo framework, which enables efficient training across loosely connected devices by significantly reducing communication requirements. Competitors include Nous Research, which has built the Hermes open-source model and recently chose Solana as its blockchain. Another emerging player is Flock.io (FLOCK), which enables financial companies like Animoca Brands and GSR, as well as healthcare companies, to train AI models in a privacy-preserving manner. While Prime Intellect and Nous Research have not yet launched tokens, Grayscale Research believes that some of these decentralized training protocols can lower costs and improve access for AI developers.

AI Model Inference — Akash

Once LLMs are trained, they can be queried by consumer applications like chatbots (e.g., ChatGPT). Each time a user asks ChatGPT a question, inference costs associated with generating output are incurred. This inference process requires complex GPU hardware (such as NVIDIA H100) to perform the necessary computations. These resource-intensive demands are often sold at high prices and under long-term contracts, making it difficult for startups, researchers, or organizations without substantial funding to afford. Meanwhile, many data centers that possess these GPUs have underutilized capacity of up to 30%.

Akash is a decentralized cloud computing GPU leasing marketplace. It allows GPU providers to monetize idle supply and enables consumers to access high-performance GPUs over flexible time periods, often at lower costs than other options.

The number of GPU leases on Akash increased from fewer than 200 before November 2024 to over 600 in January 2025, including 398 NVIDIA H100s. As a result, Akash increased its network fee revenue to an annualized $4.6 million in January of this year. Companies like brev.dev (acquired by Nvidia), Venice.ai, ElizaOS (formerly ai16z), and UT Austin are using Akash GPUs. Although Akash and similar decentralized inference platforms may not directly compete with major cloud providers, they have the opportunity to capture market share by serving startups, decentralized AI projects, independent researchers, and universities. Competitors providing similar services to Akash include io.net, Nosana, and Hyperbolic.

Figure 4: Growth acceleration of Akash fee revenue and GPU leases by November 2024

The largest DePIN asset by market capitalization is Bittensor (Figure 5), an AI-related platform we previously covered in depth. As a platform for the "AI Internet," it hosts subnetworks dedicated to tasks such as data scraping and model inference computations (the two use cases mentioned earlier). Each subnetwork acts as an independent entity within the broader Bittensor ecosystem, which operates similarly to an interconnected DePIN network. On February 13, Bittensor underwent a significant upgrade called "Dynamic TAO," which for the first time made individual subnetworks investable.

Figure 5: Examples of DePIN categorized by type, blockchain, and market capitalization

Solana as the Leading DePIN Blockchain

While many DePIN projects choose to build their own independent Layer 1 blockchains ("application chains"), Solana has become the primary blockchain for DePIN applications. By market capitalization, Solana is the leading DePIN blockchain and the preferred blockchain for many top DePIN projects (Figure 6). A notable example is Helium, which was initially built on its own Layer 1 before migrating to Solana. Similarly, the video transcoding network Render, one of the larger DePIN assets by market capitalization, migrated from Ethereum to Solana in 2024. Other DePIN projects built on Solana include Grass, Hivemapper, io.net, Nosana, and more.

Grayscale Research considers Solana the preferred DePIN chain for several reasons. First, Solana is a fast and low-cost chain that allows DePIN projects to transfer value and operate efficiently for suppliers and consumers. Second, among high-throughput and low-cost chains like BASE and SUI, Solana offers the greatest network security, liquidity, and track record. Finally, by building on Solana rather than an independent Layer 1 application chain, DePIN project developers can focus on their core competencies at the application layer without allocating resources for scaling and infrastructure-level tools and maintenance.

Figure 6: Solana is the leading blockchain for DePIN by market capitalization

Conclusion

DePIN may represent a promising frontier for blockchain technology, providing innovative solutions for global resource allocation. While some may claim that the crypto industry is limited to speculative or financial use cases, many DePIN projects offer compelling counter-evidence.

Most DePIN projects are less than five years old, but some have already shown encouraging signs of adoption, including partnerships with and services for some of the largest organizations in the world (e.g., collaborating with T-Mobile and Nvidia through brev.dev). Therefore, we are particularly excited about certain use cases, including internet connectivity, decentralized training, and networks for collecting social data or real-world physical video data for AI training. Additionally, the potential future growth of DePIN may create incremental tailwinds for Solana. As the leading DePIN blockchain, Solana provides the speed, cost-effectiveness, and security necessary for these projects to thrive.

Ultimately, we believe DePIN may represent an attractive investment opportunity. Investors interested in early, high-beta DePIN investments may consider Helium or Bittensor for wireless/IOT and AI investments, respectively. For those more inclined to hold large-cap options, we believe Solana is the preferred investment choice to grow alongside DePIN.

Glossary

Internet of Things (IoT): The Internet of Things (IoT) refers to a network of interconnected physical devices, vehicles, appliances, and other objects embedded with sensors, software, and connectivity capabilities that enable them to collect and exchange data over the internet.

DePIN: Decentralized Physical Infrastructure Networks that incentivize individuals to contribute physical infrastructure resources using blockchain and token rewards.

Blockchain: A distributed digital ledger that securely stores records across a computer network in a transparent and tamper-proof manner.

Helium: A blockchain network designed to facilitate wireless communication for global IoT devices using a unique coverage proof consensus mechanism.

Render: The native utility token of the Render Network, allowing users to share GPU capacity to render visual projects.

Grass: A protocol on the Solana blockchain that allows users to share unused internet bandwidth for network data collection, supporting AI development.

Solana: A cryptocurrency computing platform designed for high transaction speeds without sacrificing decentralization, using innovative methods like "proof of history."

Decentralized AI: The integration of AI algorithms and processes within decentralized networks, often leveraging blockchain technology to promote transparency, security, and collaboration.

Data Scraping: A technique in which a computer program extracts data from the readable output of another program.

Bittensor: A platform connecting AI and blockchain, allowing users to create or participate in competitive markets (called subnetworks).

Memecoin: A cryptocurrency created for entertainment or comedic purposes, often based on memes or humor rather than serious technological development.

Ethereum: A decentralized blockchain platform with smart contract functionality, using Ether (ETH) as its native cryptocurrency.

Data Storage: In the context of decentralized networks, data is encrypted and stored in systems across multiple locations or nodes operated by individuals or organizations sharing extra disk space.

Computing Hardware: The physical components and devices that make up a computer system, enabling it to perform various tasks and run software.

Geospatial Data Collection: The process of gathering data related to geographic locations, often used in navigation and mapping services.

Decentralized Video Streaming: A video platform that distributes content storage and streaming across multiple nodes in a peer-to-peer network using blockchain technology, reducing censorship risks and enhancing privacy.

Akash: A decentralized cloud computing marketplace that aggregates and reallocates idle computing processing power to customers in need, using AKT as its native utility and governance token.

Market Capitalization: The total value of a cryptocurrency, calculated by multiplying the total number of coins in circulation by the current price of a single coin.

LLM: Large Language Model, an advanced AI system trained on vast amounts of text data to understand and generate human-like text.

Token Rewards: Rewards provided to participants in a blockchain network in the form of cryptocurrency tokens, recognizing their contributions or activities.

Notes

[1]Artemis, Grayscale Investments, data as of Feb 18, 2025.

[2]Artemis, Grayscale Investments, data as of Feb 18, 2025.

[3]Artemis, as of Feb 18, 2025

[4]Blockworks

[5]Blockworks

[6]Messari

[7]Artemis, data as of Feb 18, 2025.

[8]Messari

[9]Prime Intellect

[10]Prime Intellect

[11]CBRE

[12]Akash Network

[13]Artemis

[14]Akash Network

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