Wall Street’s Ethereum Expansion Gains Speed As Tokenized Treasuries Top $8 Billion

bitcoinistОпубліковано о 2026-05-08Востаннє оновлено о 2026-05-08

Анотація

The market cap of tokenized U.S. Treasuries on Ethereum has reached an all-time high of approximately $8 billion, doubling in value over the past six months. This growth is driven by products from multiple institutions including BlackRock’s BUIDL, Franklin Templeton’s iBENJI, and offerings from WisdomTree, Ondo Finance, Centrifuge, and Superstate. Ethereum dominates this space, holding far more value than competitors like BNB Chain, Solana, Stellar, and the XRP Ledger. These tokenized assets are not just held as investments; they are actively used as yield-bearing collateral within decentralized finance (DeFi) protocols, providing liquidity and functionality beyond traditional bonds. While this marks a significant milestone, the $8 billion total remains a small fraction of the broader $27 trillion U.S. Treasury market. Regulatory frameworks for blockchain-based securities are still under development by financial authorities.

Six issuers are now behind the biggest milestone yet in Ethereum-based government debt.

A Market Built By Many Hands

BlackRock’s BUIDL fund, issued through Securitize, holds the largest share. But the race to $8 billion wasn’t a one-company story.

Franklin Templeton’s iBENJI, WisdomTree’s WTGXX, Ondo Finance’s USDY, Centrifuge’s JTRSY, and Superstate’s USTB all contributed to what Token Terminal now confirms is an all-time high for tokenized US Treasury products on Ethereum.

The total market cap sits at roughly $8 billion — up about 100% in just six months.

That kind of growth, spread across multiple established institutions and crypto-native platforms, points to something broader than a single firm testing the waters.

Major asset managers are building these products because they see demand. And that demand is coming from investors who want US government debt exposure with the operational advantages that blockchain infrastructure provides — faster settlement, around-the-clock access, and programmable functionality not available in traditional bond markets.

Ethereum is where nearly all of this activity is concentrated. Data from rwa.xyz shows the network leads the tokenized Treasury space by a wide margin. BNB Chain is the closest competitor, holding $3.4 billion in tokenized Treasury value. Solana, Stellar, and the XRP Ledger each hold under $1 billion.

Image: TransFi

Idle Capital Finding A New Home

One reason for the surge is how these products are being used once they’re on-chain. Tokenized Treasuries aren’t just sitting in wallets. They’re being deployed as yield-bearing collateral inside decentralized lending protocols and money markets.

That makes them functional in ways traditional bond holdings are not — and it gives DeFi participants access to a stable, government-backed asset that earns yield while remaining usable within broader financial applications.

BTCUSD trading at $81,042 on the 24-hour chart: TradingView

According to reports, the sector has matured into a multi-billion-dollar liquidity layer on Ethereum, competing directly with stablecoin reserves, money market funds, and short-term ETFs.

As more of this collateral moves on-chain, Ethereum’s total secured value grows, reinforcing its position as the primary settlement network for institutional digital assets.

Still A Fraction Of The Whole

The $8 billion figure, while record-breaking for the sector, represents a small slice of the $27 trillion US Treasury market. Regulatory questions also remain open.

Governments and financial regulators are still working through how blockchain-based securities should be governed — covering custody rules, compliance standards, and investor protections.

Featured image from ExperienceFirst, chart from TradingView

Пов'язані питання

QWhat is the total market capitalization of tokenized US Treasuries on Ethereum according to the article, and how much has it grown in the last six months?

AThe total market capitalization of tokenized US Treasuries on Ethereum is roughly $8 billion, which represents a growth of about 100% in the last six months.

QWhich six issuers contributed to the record $8 billion total for tokenized Treasury products on Ethereum?

AThe six issuers are BlackRock's BUIDL fund (via Securitize), Franklin Templeton's iBENJI, WisdomTree's WTGXX, Ondo Finance's USDY, Centrifuge's JTRSY, and Superstate's USTB.

QAccording to the article, why are major asset managers building tokenized Treasury products?

AMajor asset managers are building these products because they see demand from investors who want US government debt exposure with blockchain's operational advantages, such as faster settlement, around-the-clock access, and programmable functionality.

QBesides Ethereum, which blockchain holds the second-largest amount of tokenized Treasury value, and how much is it?

ABesides Ethereum, BNB Chain holds the second-largest amount of tokenized Treasury value, which is $3.4 billion.

QHow are tokenized Treasuries being actively used on-chain beyond just being held in wallets, as mentioned in the article?

ATokenized Treasuries are being deployed as yield-bearing collateral inside decentralized lending protocols and money markets, making them functional in ways traditional bond holdings are not and providing DeFi participants with a stable, yield-earning asset.

Пов'язані матеріали

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbit5 год тому

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbit5 год тому

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbit6 год тому

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbit6 год тому

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbit6 год тому

This is How God Karpathy Uses Claude?

marsbit6 год тому

Торгівля

Спот
活动图片