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SharpLink boosted Ethereum holdings to 837,230 ETH valued at $3.6B after $176M purchases. Despite rising ETH concentration and rewards, its stock remains volatile, as BitMine emerges with the largest corporate Ether treasury worldwide.
A platform with sound mechanisms, ample liquidity, and a vibrant, trustworthy community is more likely to provide value in terms of profitable trading opportunities and accurate predictions.
Mainstream mining algorithms include Bitcoin's SHA-256, Dogecoin/Litecoin's Scrypt, and Ethereum Classic's Ethash. Each algorithm has its specific hardware requirements and mining experience.
- Ethereum's L2 ecosystem faces operational risks as recent outages expose fragility in sequencer infrastructure and smart contract security. - Starknet's 2025 Grinta upgrade failure caused a 3-hour network freeze due to sequencer incompatibility, while Arbitrum and Base suffered outages from centralized sequencer vulnerabilities. - ZKsync's April 2025 airdrop exploit (111M tokens stolen) highlights critical security gaps, prompting price drops and exchange suspensions. - Investors must balance innovation
- Stellar Network’s Protocol 23 upgrade (Sep 3, 2025) introduces CAP-0062-CAP-0068 and SEP-0041 to enhance scalability, smart contract efficiency, and institutional performance. - Features like parallel transaction execution (CAP-0063) and Soroban Live State Prioritization reduce costs and improve throughput, targeting 5,000 TPS for enterprise adoption. - Exchange pauses (e.g., Upbit) during the upgrade highlight Stellar’s institutional relevance, while optimized fees and compliance tools position it to co
- MoonBull ($MOBU)’s whitelist presale, with 80% spots filled by August 2025, leverages FOMO and Ethereum infrastructure to drive early adoption. - High APY staking rewards (66–80%) and a 30% liquidity pool aim to balance virality with sustainability, fostering community governance. - Ethereum Layer 2 scalability and institutional-grade audits reduce risks like rug pulls, appealing to both retail and institutional investors.
- Institutional crypto portfolios shifted sharply toward Ethereum in Q3 2025, driven by its upgrades, regulatory clarity, and higher yields. - Ethereum ETFs saw $33B inflows vs. $1.17B Bitcoin outflows, with the ETH/BTC ETF ratio rising sixfold to 0.12 by July. - Whale activity confirmed the trend: $5.42B BTC-to-ETH transfers and 22% of Ethereum's supply now controlled by whales. - Ethereum's deflationary model, 4.8% staking yield, and $223B DeFi TVL outperformed Bitcoin's 1.8% yield and stagnant narrative
- Crypto markets face structural shift as whales and macroeconomic trends drive capital from Bitcoin to Ethereum. - Bitcoin's dominance fell to 57.94% amid $2.7B sell-off, while Ethereum saw $2.5B accumulation and 46.9M on-chain transactions. - Regulatory clarity (GENIUS/CLARITY Acts) and Ethereum's Layer 2 innovations boost its appeal as a settlement and tokenized asset platform. - Institutional adoption and DeFi growth highlight Ethereum's utility over Bitcoin's "digital gold" narrative in evolving crypt
- 23:13USDC Treasury mints 250 million USDCAccording to Jinse Finance, monitored by Whale Alert, at 03:56 (UTC+8) today, USDC Treasury minted 250,000,000 USDC.
- 22:32Alibaba launches more efficient Qwen3-Next AI modelJinse Finance reported that Alibaba's Tongyi Qianwen has released the next-generation foundational model architecture, Qwen3-Next, and open-sourced the Qwen3-Next-80B-A3B series models based on this architecture. Compared to the MoE model structure of Qwen3, this architecture features the following core improvements: hybrid attention mechanism, high-sparsity MoE structure, a series of training-stable optimizations, and a multi-token prediction mechanism that enhances inference efficiency. Based on the Qwen3-Next model structure, Alibaba has trained the Qwen3-Next-80B-A3B-Base model, which has 80 billion parameters but only activates 3 billion parameters. This Base model achieves performance comparable to or slightly better than the Qwen3-32B dense model, while its training cost (GPU hours) is less than one-tenth of Qwen3-32B, and its inference throughput for contexts above 32k is more than ten times that of Qwen3-32B, achieving exceptional cost-effectiveness in both training and inference.
- 22:24BlackRock plans to tokenize its funds that hold real-world assets and stocksAccording to ChainCatcher, after the success of the bitcoin ETF, BlackRock plans to tokenize its funds that hold real-world assets and stocks, and put them on the blockchain.