The Rise of AI Infrastructure Tokens: The Evolution from Layer1 to the Smart Execution Layer

According to Gate market data, as of June 26, 2026, the total market capitalization of the global cryptocurrency market is approximately $2.14 trillion, down 1.8% from the previous day. Bitcoin is priced at $59,181, and Ethereum at $1,556. The Fear and Greed Index has dropped to 13, placing the market in the "extreme fear" zone. However, amidst this period of macro-level low sentiment, a structural trend is accelerating—the deep integration of AI and blockchain infrastructure is moving from proof of concept to large-scale deployment.

This trend is not without foundation. In the first quarter of 2026, global cryptocurrency trading volume reached $20.57 trillion, with AI-generated trading activity accounting for over 15% of decentralized exchange volume, up significantly from 3% a year earlier. Since 2025, more than 17,000 AI agents have been deployed on-chain, with automated activities now accounting for approximately 19% of all on-chain transactions. Machine-to-machine payments are no longer a niche use case for blockchain but are becoming a core driver of structural transformation in the entire payment system.

Against this backdrop, AI blockchain infrastructure—from modular blockchains to AI execution layers, from decentralized computing networks to cross-chain abstraction layers—is undergoing a systematic restructuring from the underlying architecture to the application layer. This evolution logic is unpacked from three dimensions, using projects like Heima (HEI) as examples to illustrate the current landscape and future direction of the infrastructure track.

Modular Blockchain: The "Lego-like" Foundation for the AI Era

In 2026, public chains are fully transitioning from monolithic architectures to modular designs that decouple consensus, execution, data availability (DA), and settlement layers. The core driving force behind this shift is that AI applications have placed entirely new performance requirements on blockchain infrastructure.

Traditional monolithic chain architectures are showing shortcomings in scalability, cost, and flexibility. The core idea of modular blockchain is layered decoupling, splitting the system into four independent modules: consensus layer, data availability layer, execution layer, and settlement layer. Each module performs its own function and works collaboratively, with no single chain bearing all functions. The consensus layer handles node consensus across the network, ensuring security and decentralization; the data availability layer stores on-chain raw data, ensuring data can be queried and verified; the execution layer focuses on processing transactions and smart contract computations, handling core business logic; and the settlement layer completes final transaction confirmation and asset liquidation.

The performance improvements brought by this architecture are substantial. Compared to traditional monolithic blockchains, the modular architecture increases overall transaction processing capacity by more than three times and reduces on-chain fees by up to 70%. More importantly, the new chain deployment cycle has been shortened from six months to two weeks, with costs reduced by 85%. With the independence of the data availability layer, solutions like EigenDA reduce on-chain storage costs by 90%, supporting millions of TPS.

The maturity of benchmark projects further validates this trend. Celestia, through its Matcha upgrade in Q1 2026, doubled its block size to 128 MB, solidifying its technological leadership in the data availability layer. EigenLayer, leveraging its restaking ecosystem, essentially builds a data availability service layer relying on Ethereum's validator set. Polygon CDK offers modular development tools for developers, lowering the barrier to building customized blockchains.

The significance of modular architecture for the AI ecosystem is profound. AI agents require a high-frequency, low-cost transaction environment for micropayments, data procurement, and computing power settlements—these scenarios demand far higher throughput and fee sensitivity from the execution layer than traditional DeFi applications. Modular blockchain makes it possible to create execution layers tailored for AI scenarios, providing the underlying feasibility for large-scale deployment of native AI applications.

AI Execution Layer: From Auxiliary Tool to Independent Economic Entity

If modular blockchain answers the question "how to make the underlying layer more efficient," then the AI execution layer addresses "how the upper layer operates."

Between May 2025 and April 2026, AI agents completed approximately 176 million transactions across multiple blockchain networks, with a total settlement amount exceeding $73 million and a median single payment value ranging from $0.31 to $0.48. As of Q1 2026, over 104,000 AI agents have been registered. These data reveal a clear fact: AI agents are evolving from information processing tools into independent economic participants.

This transformation has given rise to a core infrastructure need—the execution layer. Traditional transaction infrastructure is designed with the assumption that "humans operate interfaces"—market displays, order confirmations, asset transfers—every step is based on the cognitive pace and operating habits of human users. But when participants shift from humans to AI, these assumptions break down. What AI needs is not scattered API interfaces, but a unified, protocol-level capability layer that can complete the entire loop of data acquisition, strategy judgment, transaction execution, and result monitoring within a single framework.

Against this backdrop, a number of projects focused on the AI execution layer have emerged. Nesa positions itself as a lightweight Layer-1 blockchain, specifically designed to provide a distributed execution environment for AI inference tasks requiring high privacy, security, and trust, allowing developers to run multimodal models without trusting a single server or centralized platform. Alphea, at the 2026 Hong Kong Web3 Summit, released an AI-Native Layer-1 execution network, building a decentralized runtime environment for autonomous AI agents, integrating local execution, dynamic storage, execution proofs, and a usage-based economic model into a single infrastructure layer. The collaboration between VectorAI and AIW3 aims to achieve scalable decentralized execution of AI agents across multiple blockchain networks.

The independent execution layer is a natural extension of the modular blockchain trend. When the execution layer can be separated from the consensus and settlement layers and specifically optimized for AI workloads, the economic activities of AI agents are no longer constrained by the performance bottlenecks of general-purpose blockchains. This provides the infrastructure premise for the large-scale operation of the machine-to-machine economy.

Decentralized Computing Networks: Web3 Solutions to the "Computing Power Shortage"

"Computing power, algorithms, and data" are the three core elements of AI development, and the strategic value of computing power has been elevated to unprecedented heights in 2026. The "computing power shortage" is no longer just a long-term industry warning but has become the primary bottleneck constraining AI progress.

Globally, high-end NVIDIA GPU rental prices continue to rise, hardware supply remains chronically tight; leading AI companies like OpenAI and Anthropic often experience server outages due to insufficient computing power reserves. SpaceX, which recently listed on Nasdaq, admitted in its IPO prospectus that the computing power required for its business-supporting AI systems has already far exceeded current market supply. Microsoft's Azure cloud platform was also reportedly forced to urgently request computing power from competitor Amazon AWS. AI labs at top universities like Stanford and MIT have also suspended multiple large model training projects due to insufficient computing power.

It is precisely against this backdrop that decentralized computing networks, as an important component of Web3 infrastructure, have begun offering differentiated solutions.

On June 17, 2026, BitTorrent announced the launch of its core AI strategic product, BTTInferGrid, building a decentralized computing network for AI inference scenarios. BTTInferGrid is a strategic upgrade based on its mature decentralized storage service BTFS, adopting a three-layer collaborative architecture of "application layer—computing layer—settlement layer." It aggregates globally dispersed idle GPU computing resources in a decentralized manner, precisely matching the inference needs of AI developers. On June 22, Eigen Labs launched Darkbloom, a decentralized AI inference network utilizing idle Apple Silicon Macs. Through a coordinator routing AI requests, suppliers can run models without accessing data.

The value logic of decentralized computing networks lies in using crypto-economic incentives to transform globally idle computing power into programmable resources, breaking down the barriers and monopolies formed by traditional centralized computing service providers. This model not only reduces the cost of acquiring computing power for AI developers but also creates new revenue sources for computing providers. From an infrastructure perspective, decentralized computing networks are becoming a key hub connecting "computing resources" with "on-chain execution" in the Web3 architecture.

Cross-Chain Abstraction and Agent Economy: Heima (HEI) Infrastructure Positioning

In the landscape of AI blockchain infrastructure, cross-chain interoperability is an indispensable component. AI agents will not be confined to running on a single blockchain—they need to allocate assets, settle fees, and coordinate resources across different chains. This places demands for abstraction and unification on cross-chain infrastructure.

Heima (HEI) is a Layer-1 blockchain and cross-chain infrastructure project positioned precisely for this purpose, aiming to unify and abstract the fragmented blockchain ecosystem. In March 2026, Heima announced its participation in the Agentic Economy, committed to building a non-custodial infrastructure that allows AI agents to freely trade in a verifiable on-chain economy. Heima provides TEE secure execution through a secure agent infrastructure, ensuring protection of user-sensitive logic and private memory, while integrating with x402 to ensure programmable payment primitives.

From a tokenomics perspective, the Heima community voted on June 6, 2026, to approve the burning of 16.5 million HEI tokens, including 12.1 million locked HEI and 4.45 million unlocked but unused HEI. This fund was originally reserved for Polkadot parachain auctions; since Polkadot switched to Coretime sales, Heima stated it could use the DOT treasury reserved by the team to cover related costs.

As of June 26, 2026, according to Gate market data, the price of Heima (HEI) is $0.17269, up 40.71% in 24 hours, 56.59% in 7 days, and 182.46% in 30 days. Its 24-hour trading volume is $5.6867 million, total supply is 92.8592 million tokens, and market cap is approximately $11.6766 million. Market sentiment rating is neutral. Over the past 90 days, the HEI price has risen from a low of $0.05496 to a high of $0.27150, an increase of 126.73%.

The case of Heima reveals a key characteristic of the AI blockchain infrastructure track: the value of an infrastructure project lies not only in its technical architecture, but also in whether it can become a verifiable and trustworthy settlement and coordination layer in the AI agent economy. As AI agents evolve from auxiliary tools to independent economic entities, demand for cross-chain abstraction layers and secure execution environments will continue to grow.

Market Divergence and the Value Logic of Infrastructure

It is worth noting that the integration of AI and crypto is not a uniformly rising curve. During the market correction in Q1 2026, the "AI Agent token" label experienced an overall decline of around 80% to 90%, but this decline was selective. Tokens with "AI" in their name but no practical use completely collapsed, while projects with actual usage rates remained stable or even rose. The overall size of the AI crypto sector still grew approximately threefold, from about $9 billion at the beginning of 2025 to about $22–$27 billion in May 2026.

This divergence sends a clear signal: the market is shifting from narrative-driven to utility-driven. For AI blockchain infrastructure projects, this means that technical implementation capability, actual user adoption rates, and verifiable economic activity are replacing concept packaging as the core of valuation. Modular blockchain solves the underlying scalability issue, the AI execution layer solves the agent runtime environment issue, and decentralized computing networks solve the computing power supply issue—the co-evolution of these three is building a complete technology stack for the large-scale operation of the AI agent economy.

From a market size perspective, the blockchain AI market grew from $700 million in 2025 to $900 million in 2026, a compound annual growth rate (CAGR) of 27.8%; another statistic shows the market reached $4.8 billion in 2026. The Web3 infrastructure market grew from $5.41 billion in 2025 to $7.55 billion in 2026, a CAGR of 39.6%. Although statistical scopes differ, the trend of rapid growth is consistent.

Conclusion

The crypto market in 2026 is at the intersection of macroeconomic headwinds and structural transformation. Bitcoin's price hovers around the $60,000 mark, market sentiment is in extreme fear, but the underlying construction of AI blockchain infrastructure has not slowed down. Modular blockchain has made the leap from concept to scale, the AI execution layer has moved from theory to practice, and decentralized computing networks have begun to address real computing power shortages.

The core driving force behind this round of infrastructure restructuring is the rise of AI agents as a new type of economic entity. When machines begin to autonomously complete transactions, settlements, and resource allocation, blockchain is no longer just a carrier of assets but becomes the settlement layer and trust layer of the machine-to-machine economy. From Celestia's data availability to Nesa's AI execution layer, from BTTInferGrid's decentralized computing power to Heima's cross-chain abstraction, the co-evolution of these infrastructure layers is building a composable, scalable, and verifiable technical foundation for the next-generation Web3 ecosystem.

For industry observers, the second half of 2026 requires attention not only to price fluctuations but also to the substantive progress of these infrastructure projects in technical implementation and actual adoption rates. The pendulum of market sentiment will eventually swing back, and infrastructure layers with genuine utility support will occupy a more solid value position in the next cycle.

FAQ

Q: What is AI blockchain infrastructure?

AI blockchain infrastructure refers to the blockchain technology stack that provides underlying support for AI applications, including modular blockchain architectures, AI execution layers, decentralized computing networks, data availability layers, and cross-chain interoperability protocols. Its core goal is to provide a scalable, low-cost, and verifiable on-chain runtime environment for the autonomous economic activities of AI agents.

Q: What is the relationship between modular blockchain and the AI execution layer?

Modular blockchain splits the traditional monolithic chain into four independent modules—consensus, data availability, execution, and settlement—among which the execution layer can be specifically optimized for AI workloads. The AI execution layer is a natural extension of the modular architecture at the application layer, providing a dedicated runtime environment for AI agents for high-frequency transactions, micropayments, and smart contract interactions. Together, they form the infrastructure foundation for native AI applications.

Q: How do decentralized computing networks solve the AI computing power shortage?

Decentralized computing networks aggregate globally idle GPU computing resources into a programmable computing market through crypto-economic incentives. AI developers can obtain inference computing power on demand, while computing providers contribute idle resources and earn token rewards. This model breaks the supply monopoly of traditional centralized cloud service providers, reduces the cost of acquiring computing power, and improves resource utilization efficiency.

Q: What role does Heima (HEI) play in the AI blockchain infrastructure ecosystem?

Heima is a Layer-1 blockchain and cross-chain infrastructure project dedicated to unifying the fragmented blockchain ecosystem, providing a non-custodial, verifiable transaction environment for AI agents. Its core functions include cross-chain abstraction, TEE secure execution, and programmable payments, enabling AI agents to freely allocate assets and settle fees across different blockchain networks. It serves as a key coordination and security layer in the agent economy.

Q: What are the main trends in the AI blockchain infrastructure track in 2026?

The core trends in 2026 include: public chains fully transitioning from monolithic to modular designs; the AI execution layer evolving from an auxiliary tool to an independent infrastructure component; decentralized computing networks accelerating deployment to address global computing power shortages; and the market shifting from narrative-driven to utility-driven, with the valuation divergence between projects with actual usage rates and pure concept projects continuing to widen.