NEAR Investment Logic Reassessed: Trading Volume Has Taken Off, Can Token Value Keep Up?

NEAR pivots to AI and chain abstraction

TL;DR

NEAR's investment logic is shifting from a high-performance Layer 1 to chain abstraction, cross-chain settlement, and AI agent infrastructure, seeking greater growth from the multi-chain ecosystem.

NEAR Intents has reportedly completed over $13 billion in cross-chain settlement, but a significant gap remains between settlement volume and actual protocol revenue.

NEAR's maximum annual inflation rate has been reduced from 5% to about 2.5%, while developer gas rebates have been eliminated and fee burning expanded, improving tokenomics compared to the previous cycle.

In the 30 days before Sept. 1, NEAR-related products generated about $3.48 million in total fees, but net protocol fees were only about $757,500, indicating value capture is still in its early stages.

The founding team has genuine AI and distributed systems backgrounds, but AI products, partnerships, and user growth have yet to demonstrate sustained commercial revenue.

NEAR still lags behind Ethereum and Solana in liquidity, developer scale, and application network, and also faces competition from Sui, Aptos, and other cross-chain infrastructure.

Current derivatives market is broadly bullish, but open interest is declining, suggesting the recent rally may be partly driven by short covering.

NEAR is better viewed as a high-beta, high-execution-risk optionality investment rather than a core asset with stable cash flow and network moat.

NEAR is undergoing a significant strategic shift.

Previously, NEAR competed primarily as a high-performance Layer 1, with selling points centered on sharded scaling, low fees, and fast confirmation. Now, it aims to reposition itself as the underlying infrastructure for multi-chain transactions and AI agents: users no longer need to understand the complex structure of blockchains, as wallets and agents can automatically complete cross-chain transfers, swaps, and payments.

NEAR Intents has already provided preliminary transaction data for this direction, and the AI business has gained market attention due to the founding team's technical background. At the same time, NEAR has reduced inflation, expanded fee burning, and attempted to use product revenue for token buybacks.

The problem is that these developments have not yet fully translated into sustained demand for the NEAR token. Transaction volume can grow rapidly, but the protocol's actual revenue may be limited; AI products can use NEAR's technology, but that does not mean users must hold NEAR.

This makes NEAR a highly representative crypto asset: the technical direction is becoming increasingly clear, but the economic loop remains unproven.

From a single chain to a multi-chain transaction gateway

NEAR was originally a general-purpose smart contract platform for consumer applications. Its Nightshade architecture processes network state through sharding, aiming to expand capacity while maintaining low costs. According to project disclosures, NEAR's current block time is about 600 milliseconds, with finality in about 1.2 seconds; in 2025, the number of network shards increased from 6 to 9, raising theoretical throughput by about 50%.

These performance metrics are not bad, but in today's public chain market they hardly constitute an independent advantage. Solana, Sui, Aptos, and Ethereum Layer 2s are all offering faster and cheaper transaction experiences. For NEAR, continuing to emphasize TPS and fees would only trap it in homogeneous competition.

Therefore, NEAR has begun shifting its development focus to "chain abstraction."

Simply put, chain abstraction aims to make users unaware of which blockchain they are using, and eliminate the need to manually handle cross-chain bridges, gas tokens, and transaction routing. Users only need to state the outcome they desire, and the system can automatically find the appropriate network, liquidity, and execution plan.

NEAR Intents is the most important product in this strategy. Traditional cross-chain transactions typically require users to choose a bridge, exchange, and destination network; in the Intents model, users only need to submit a transaction intent, and solvers then find the optimal path across different platforms and liquidity pools.

Data disclosed by NEAR shows that Intents' cumulative cross-chain settlement volume has exceeded $13 billion. Some community statistics estimate $20 billion to $26 billion, covering 30 to 35 blockchains. Although different data may use different time ranges and statistical standards, it at least indicates that NEAR Intents has achieved a certain scale of real transaction activity.

This also changes NEAR's potential market. Previously, a public chain's growth relied mainly on developers deploying applications on its own chain, then attracting users and capital; if the Intents model works, NEAR could participate in asset flows on other blockchains even without hosting all applications, and earn revenue from cross-chain transactions.

However, chain abstraction has an inherent contradiction: the smoother the user experience, the more the underlying network is hidden. Users may use NEAR's execution capabilities without knowing that transactions passed through NEAR, and without needing to directly hold NEAR tokens.

Meanwhile, wallets, aggregators, cross-chain protocols, and other intent networks are all competing for the transaction gateway. Even if NEAR Intents' settlement volume continues to expand, most fees may flow to solvers, market makers, and partner applications that provide quotes and liquidity. How much revenue NEAR can retain is the key determinant of its valuation.

AI provides a new narrative, but commercial revenue still needs validation

AI is another main thrust of NEAR's strategic shift.

NEAR is laying out autonomous agents, confidential model execution, verifiable AI outputs, agent marketplaces, machine-to-machine payments, and user-owned AI assistants. The project aims to combine blockchain's account, payment, and asset ownership capabilities with the autonomous execution capabilities of AI agents.

Compared to some crypto projects that only repositioned after the AI boom, NEAR indeed has a more direct technical foundation. Co-founder Illia Polosukhin previously conducted machine learning research at Google and co-authored the seminal Transformer paper "Attention Is All You Need"; co-founder Alexander Skidanov has experience in distributed databases and large-scale systems development.

This gives NEAR's AI pivot a degree of continuity, rather than merely seeking a hotter market label for its token.

According to project disclosures, NEAR's AI ecosystem already involves more than 50 teams, covering research, data, storage, models, and applications. Related collaborations or integrations include Frax, Infinex, SWEAT, and Eliza. NEAR is also advancing AI assistants such as IronClaw, aiming to use trusted execution environments, credential isolation, and privacy protection to enable agents to securely access accounts, hold assets, and execute transactions.

There is also a natural synergy between AI and Intents. Future AI agents may need to autonomously purchase services, manage funds, and exchange assets across different blockchains. Intents can help agents find paths and liquidity, and NEAR has the opportunity to become the coordination and settlement layer for these machine-to-machine transactions.

The imagination space is large, but commercial evidence remains limited. Having 50 AI teams does not mean having 50 mature revenue sources, and partnerships and product launches do not represent stable paid demand. Centralized AI services already have mature computing power, tools, and enterprise customers; NEAR must prove that the asset ownership, privacy, and verifiability brought by blockchain are sufficient to offset the additional technical complexity.

More importantly, even if AI products succeed, value may not accrue to the NEAR token. Agents may access services through third-party wallets, fees may be paid by applications on behalf of users, and end users may not need to purchase or hold NEAR long-term. Whether AI activity can generate protocol revenue, and whether that revenue can create token demand, remain two questions that have not been fully answered.

$13 billion in trading volume, how much revenue remains?

The most noteworthy aspect of NEAR's current investment logic is not the transaction volume itself, but the gap between transaction volume and protocol revenue.

According to the revenue dashboard cited in the original text, in the 30 days before Sept. 1, 2026, NEAR-related products generated about $3.48 million in total fees. After deducting payments to solvers, partners, applications, and other participants, net protocol fees were about $757,500.

In other words, the revenue actually retained by the protocol is only a portion of total fees. This distribution is not surprising: cross-chain transactions require solvers to provide quotes, market makers to provide liquidity, and applications and wallets also need to earn revenue. But for NEAR token holders, cross-chain transaction volume and total fees are not the most important numbers; net protocol revenue is closer to the economic value that the underlying asset can capture.

Even so, net fees cannot be directly equated with shareholder cash flow. NEAR can use revenue for buybacks, staking, locking, ecosystem spending, or the protocol treasury, but there is currently no fixed rule requiring all revenue to be used to purchase tokens. Fund usage remains subject to governance decisions.

Therefore, when observing NEAR's fundamentals, looking only at user numbers, transaction counts, or Intents settlement volume can easily overestimate growth quality. The three questions that truly matter are: Is net protocol revenue growing sustainably; is the proportion of revenue to total transaction fees increasing; and how much of this revenue ultimately translates into NEAR purchases, burns, or long-term locking demand.

If Intents settlement volume grows rapidly while net revenue remains persistently low, NEAR could become a heavily used infrastructure without necessarily being an asset that effectively captures value.

NEAR has also been trying to address this issue in recent years. Its maximum annual inflation rate has been reduced from 5% to about 2.5%; the developer gas rebate mechanism has been eliminated, with related transaction fees more fully entering the burn process; NEAR Intents has also activated a fee switch and attempted to use part of product revenue for buybacks. According to project disclosures, these mechanisms have driven buybacks of over 1 million NEAR.

Supply structure has also improved. Approximately 1.305 billion NEAR tokens are fully or nearly fully circulating, with circulating market cap essentially equal to fully diluted valuation. Compared to new public chains that still have large amounts of team and investor tokens waiting to unlock, NEAR faces lower concentrated unlock pressure in the future.

But near-full circulation does not equal deflation. NEAR's fees are low, and even with high transaction volume, the burn scale may be insufficient to offset the issuance from validator rewards. Buybacks also have a degree of discretion and have not yet formed a stable, predictable institutional arrangement.

NEAR needs to prove not just that tokenomics have "improved," but that protocol revenue and fee burns can eventually approach or exceed new issuance. Only when this loop is closed can product growth be reliably transmitted to token value.

Ecosystem still growing, but leadership not yet established

NEAR's published user and transaction data are quite impressive. Its 2024 review shows that monthly active users grew from 7 million the previous year to 40 million, daily active users were about 4 million, and average daily transactions exceeded 8 million. Ecosystem projects raised about $146 million in external funding that year, and accelerator participating teams raised about $50.5 million.

These data at least indicate that NEAR is not a "ghost chain" that has lost developers and users. After the previous bear market, it still retains its network, infrastructure, capital, and application ecosystem.

But blockchain user metrics need to be interpreted cautiously. So-called monthly active users may refer to accounts, addresses, or application interaction entities, which may include automated programs, subsidized activities, and low-value transactions, and cannot be directly understood as unique users on internet platforms.

The original text also did not obtain complete, independently verified latest data on user retention, stablecoin scale, TVL, and transaction quality. Therefore, 40 million monthly active users and 8 million daily transactions can prove network activity, but cannot alone prove that this activity will generate sustained revenue.

Developer data presents a similar picture. August 2026 data cited in the original text shows that the NEAR ecosystem has about 1,231 developers, 79,400 code commits, and 234 repositories. By the same statistical standard, Solana has about 1,494 developers, while Ethereum reaches 11,600.

NEAR clearly has a functioning developer ecosystem, but the gap with Ethereum remains significant, and it also lags behind Solana in liquidity and consumer application momentum. Applications such as HOT Wallet, SWEAT, and KAIKAI have brought NEAR a certain user base, but have not yet formed a killer product capable of changing the industry landscape.

NEAR's competition also spans multiple markets. In the base layer space, it competes with Ethereum, Solana, Sui, and Aptos for developers and capital; in chain abstraction, it faces wallets, transaction aggregators, cross-chain bridges, and other intent networks; in AI, it must also compete with centralized cloud service providers and crypto projects focused on computing power, data, models, and privacy.

This gives NEAR both significant optionality and high execution risk. If synergies form among its multiple product lines, NEAR could build a complete system covering accounts, payments, cross-chain, and agents; if resources are overly dispersed, it could end up with many products but persistently limited market position.

NEAR currently resembles a technically credible, differentiated mid-sized competitor rather than a market leader with a strong moat.

Core judgment: NEAR needs to prove more than just technology

NEAR's most attractive investment logic at present is to become the coordination, transaction, and settlement infrastructure in the multi-chain and AI agent economy. If this vision is realized, the market NEAR can cover may be far larger than a single Layer 1, and it could establish new value capture paths through Intents fees, agent payments, and token buybacks.

NEAR's advantages include a strong founding team, long operating record, sharded architecture, near-fully circulating token structure, reduced inflation rate, and a differentiated direction formed by AI and chain abstraction.

But its biggest risk may not be technical failure, but rather remaining in a state of "technically reliable, product-rich, but economically secondary." NEAR could continue to operate stably, maintain its developer community, and keep launching new products, yet never form a sufficiently strong application network, protocol revenue, and token demand.

The most important metrics to track going forward include NEAR Intents net revenue and margins, non-incentivized user retention, stablecoin and TVL growth, real commercial revenue from AI products, effective token inflation rate, and transparency of buybacks and treasury funds.

Ultimately, NEAR needs to answer three questions: How much revenue can Intents' transaction growth retain for the protocol; will AI and cross-chain products create direct NEAR token demand; and can protocol revenue, burns, and buybacks offset new issuance over the long term.

Until these questions are sufficiently validated, NEAR is better viewed as a high-beta asset betting on the development of AI and multi-chain infrastructure. Its technical foundation and product direction offer significant upside, but commercialization capability, value capture, and competitive pressure still determine whether this transformation can truly bring about a valuation re-rating.