Weekly Token Unlocks: STRK Unlocks 4% of Circulating Supply but Price Surges

marsbitОпубліковано о 2026-05-10Востаннє оновлено о 2026-05-10

Анотація

Weekly Token Unlock Recap: STRK's 4% Supply Release Sees Price Rally This week's major token unlocks featured two prominent Ethereum scaling solutions: **Starknet (STRK):** Approximately 130 million STRK tokens (4% of circulating supply), valued at roughly $7.19 million, were unlocked. Starknet is an Ethereum Layer 2 network utilizing zk-STARKs technology to enable faster and cheaper transactions. Despite the significant supply increase, the token's price experienced an upward movement. **Arbitrum (ARB):** Around 95.87 million ARB tokens, worth approximately $13.71 million, were released. Arbitrum is another leading Ethereum Layer 2 solution that processes transactions off-chain before bundling them for Ethereum mainnet settlement, offering improved scalability and lower costs. The ARB token grants holders governance rights within the ecosystem. Both projects continue to play significant roles in scaling the Ethereum network.

Starknet

Project Twitter: https://twitter.com/Starknet

Project Website: https://starknet.io/

Tokens Unlocked This Round: 130 million

Value of Unlocked Tokens: Approximately $7.19 million USD

Starknet is a Layer 2 for Ethereum, utilizing zk-STARKs technology to make Ethereum transactions faster and cheaper. Its parent company, StarkWare, was founded in 2018 and is headquartered in Israel. StarkWare's main products include Starknet and StarkEx. By using STARKs, Starknet verifies transactions and computations without requiring every network node to validate each operation. This significantly reduces the computational load and increases the throughput of the blockchain network.

Arbitrum

Project Twitter: https://twitter.com/arbitrum

Project Website: https://arbitrum.io/

Tokens Unlocked This Round: 95.87 million

Value of Unlocked Tokens: Approximately $13.71 million USD

Arbitrum is an Ethereum Rollup designed to enhance Ethereum's scalability. It aggregates and processes transactions off-chain before submitting a single transaction to the Ethereum mainnet. This means users can enjoy faster and cheaper transactions while still benefiting from the security and decentralization of the Ethereum network. The native token of Arbitrum is ARB. ARB holders can participate in the decision-making process, such as proposing and voting on protocol upgrades or changes.

Пов'язані питання

QAccording to the article, which project will unlock 1.3 billion tokens this week?

AAccording to the article, Starknet (STRK) will unlock 1.3 billion tokens this week.

QWhat is the approximate USD value of Arbitrum's (ARB) token unlock mentioned in the article?

AThe approximate USD value of Arbitrum's token unlock mentioned in the article is $13.71 million.

QWhat core technology does Starknet use to scale Ethereum transactions?

AStarknet uses zk-STARKs technology to scale Ethereum transactions, making them faster and cheaper.

QWhat is the primary purpose of the Arbitrum network as described in the text?

AThe primary purpose of the Arbitrum network is to increase Ethereum's scalability by aggregating and processing transactions off-chain before submitting them to the Ethereum mainnet.

QWhat role do ARB token holders have within the Arbitrum ecosystem?

AARB token holders can participate in governance, such as proposing and voting on protocol upgrades or changes within the Arbitrum ecosystem.

Пов'язані матеріали

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

A discussion on Zhihu about "AI relay stations" shifted the niche developer topic of "cheap tokens" into broader user awareness. Users moved beyond simply questioning the legitimacy of these services to focus on practical concerns: Where do cheap tokens truly come from? Is the model being accessed the real one? Can relay stations see prompts, code, and API keys? For occasional users, are the risks worth it? The core debate centered less on price and more on trust. A primary worry is model authenticity—the risk of "model swapping," where users paying for a premium model might be routed to a cheaper one, creating an information asymmetry. Others argued that cost comparisons matter; while cheaper than official pay-as-you-go APIs, relay stations may not be the lowest-cost option versus subscriptions, domestic models, or free tiers, making user needs assessment crucial. Speculation about token sources ranged from legitimate bulk discounts to gray-area methods like account sharing or exploiting regional pricing. This opacity makes risk assessment difficult for users. Data security emerged as a critical concern, especially for enterprise use. When processing sensitive information like code, contracts, or client data, the inability to verify a relay station's data handling, retention, or access policies poses significant compliance and confidentiality risks. The evolving consensus suggests relay stations can be used cautiously for low-sensitivity, disposable tasks (e.g., summarizing public info, simple translation). However, they should not be the default for sensitive, professional, or production workflows involving proprietary data, Agents, or automated systems. Recommendations include avoiding large prepayments, not relying on a single service, using test prompts to monitor quality, anonymizing data where possible, and keeping official channels as backups. Ultimately, the discussion framed tokens not just as a billing unit but as a measure of real cost encompassing price, model integrity, data security, and service stability. The popularity of relay stations highlights user demand for affordable access, but the debate underscores a key trade-off: the savings from cheap tokens may come at the price of trust, transparency, and control over one's data and AI experience.

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In-Depth Research Report on TradFi: The Convergence Wave of Crypto and Traditional Finance

In 2026, the crypto industry is undergoing a profound infrastructure-level transformation—TradFi assets are migrating on-chain at an unprecedented pace. According to CoinGecko's Q1 2026 report, the total value locked (TVL) of tokenized real-world assets (RWA) has surpassed $31 billion, a nearly 4x increase from $7.8 billion at the beginning of 2025, with the sector’s aggregate market capitalization reaching $19.3 billion. Among these, the market cap of tokenized stocks surged from $2 million to $486 million, with Q1 spot trading volume reaching $15.1 billion—a single quarter already surpassing the entire second half of 2025. RWA perpetual contract Q1 trading volume reached a staggering $524.8 billion, far exceeding the $313 billion for all of 2025. Meanwhile, BlackRock's BUIDL fund has reached $2.3 billion in scale and has filed for two new tokenized funds, signaling that the world's largest asset manager's tokenization strategy is evolving from pilot to product suite expansion. HTX, as a core participant in the crypto exchange sector, officially launched TradFi perpetual futures products including NVDA, AAPL, MSFT, META, and SPY in 2026, enabling crypto users to gain 24/7 trading access to core U.S. equities. Boston Consulting Group predicts that global tokenized asset scale could reach $16 trillion by 2030, while McKinsey offers a conservative estimate of approximately $2 trillion. The on-chain migration of TradFi assets is no longer a "future narrative" but a structural transformation unfolding in real time, as crypto exchanges evolve from single crypto asset trading platforms toward "multi-asset-class trading infrastructure."

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Blocked Its Own Treasure, WeChat AI Steps Up

Tencent's stock surged over 10% on June 2nd amid reports that WeChat, with 1.43 billion monthly users, is finalizing tests for a native AI Agent. The reported feature, accessible by swiping right from the main interface, allows users to issue commands in natural language. The AI then decomposes tasks and automatically calls upon relevant Mini Programs within WeChat to complete actions like ordering food, booking tickets, or making payments, creating a closed-loop service execution system. This strategic shift follows the internal conflict and subsequent "blocking" of Tencent's standalone AI app, Yuanbao, by WeChat for violating sharing rules during a 2026 Spring Festival promotion. The incident highlighted a lack of internal consensus and exposed the weakness of competing in the standalone AI assistant arena against rivals like ByteDance's Doubao (345M MAU) and Alibaba's Qianwen. The new WeChat AI Agent aims to leverage WeChat's unique assets—its massive user base, standardized Mini Program APIs, WeChat Pay, and identity system—to move from simple content generation to actual task execution. Analysts note this changes the competitive landscape from model benchmarks to which AI can connect to more real-world services. However, success depends on key variables: the capability of Tencent's underlying Hunyuan model, managing massive inference costs, and redesigning incentives for Mini Program developers whose traffic might be bypassed. The move is seen as an attempt to keep user service intent within WeChat's ecosystem as AI begins to redefine how users access services.

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ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

**Summary:** At Computex 2026, Arm CEO Rene Haas announced that ByteDance and Oracle have adopted Arm's self-designed Arm AGI data center CPU. The company expects significant revenue growth from this product, projecting $20 billion in demand for the 2027/2028 fiscal years. Haas noted that restricting AI-capable CPUs from the US to China is nearly impossible due to their widespread applications. Arm's stock has surged dramatically this year, notably rising 16% after NVIDIA's Arm-based Vera CPU and RTX Spark announcements. A highlight was the informal, humorous on-stage conversation between Haas and NVIDIA CEO Jensen Huang. Huang joked about NVIDIA's failed attempt to acquire Arm and playfully lamented selling his Arm shares. Both executives showed a clear sense of camaraderie and shared regret over the missed merger. Key technical topics were discussed: 1. **AI PC Design:** Huang explained NVIDIA's RTX Spark superchip (with a 20-core Arm CPU) is designed for future AI agents that will autonomously run and use tools on PCs, blending local and cloud processing. 2. **Agent vs. OS:** Huang emphasized the operating system remains crucial, as AI agents rely on its APIs and tools to function. 3. **Growth Constraints:** He identified the shift to "useful AI" that generates profitable tokens as a primary driver for immense, almost limitless, computational demand. Haas outlined Arm's strategy across PC and data centers. For PCs, Arm collaborates with partners like NVIDIA and MediaTek, offering its compute subsystem (CSS) for custom SoCs. In data centers, its Arm AGI CPU (built on TSMC's 3nm process) has gained major partners including OpenAI, Meta, and now ByteDance and Oracle. Arm presented a multi-year roadmap for its in-house CPU line. The article concludes that while GPUs dominated the AI training race, the explosion of AI agents is shifting significant focus to CPUs for inference, state management, and tool orchestration. The industry is trending towards vertical integration, with companies like cloud providers designing chips and chip/IP firms offering full solutions, all competing to deliver more efficient computing per watt.

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