以太坊多头掌、接下来怎么走?XRP大跌或探2.15美元、KAS、SUI要反弹LTC、LINK看涨结构显现

金色财经Pubblicato 2025-08-01Pubblicato ultima volta 2025-08-01

以太坊多头主导,突破 3965 美元或创新高

以太坊在 3700 美元上方反弹后进入盘整,多头仍控制市场。此前突破 2800-2880 美元阻力位后,图表结构转向看涨,价格维持在 3273 美元上方显示势头持续。当前焦点在 3965 美元关键阻力位,突破后可能冲击历史新高;回调时 3273-3370 美元区间将提供强支撑,只要该区域稳固,上涨趋势技术上有效。

XRP 回落寻支撑,买家犹豫或跌至 2.15 美元

XRP 曾涨至 7 年新高后回落,受整体市场看跌情绪影响。分析师指出,其上涨由大量买盘推动,但突破 2024 年高点后遇阻,高价位多头被套。更值得注意的是,价格创新高时交易量明显下降(2024 年破 3 美元时交易量 780 亿美元,此次破 3.6 美元仅 410 亿美元),购买兴趣减弱。

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若买家未能发力,XRP 可能从 2.95 美元进一步回落,下一看跌目标 2.15-2.3 美元(被视为 “合适入场位”),更深可能至 1.60-1.93 美元;若有买盘支撑,仍有望回升至 4.64 美元。

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KAS 和 SUI 显反弹信号,技术形态积极

Kaspa 本月上涨 25.57%,从半年 27.19% 的跌幅中恢复,但近一周跌 9.24%,波动性明显。当前交易区间 0.0595-0.0916 美元,支撑位 0.0438 美元,阻力位 0.1078 美元。

RSI 51.28 呈中性,动量指标略偏空,短期情绪改善但长期仍有挑战。

SUI 近期涨 38.55%,周涨 3.54%,但半年跌 5.71%,短期反转信号显现。价格在 2.19-3.48 美元波动,测试 4.19 美元阻力和 1.59 美元支撑。

振荡指标略偏多,RSI 54.22 显示多空平衡,缺乏明确趋势但存在战术机会。

LTC 和 LINK 看涨结构显现,或迎囤币期

Chainlink 近月涨 35%,半年跌 28%,当前区间 11-15.70 美元,阻力 18.03 美元,支撑 8.63 美元。

振荡指标略偏多,但动量指标为负,多头暂控市场但空头压力仍在,需关注区间突破机会。

莱特币近月涨 29%,半年跌 13%,交易区间 76.80-94.61 美元,阻力 103.27 美元,支撑 67.65 美元。

RSI 接近 60 显示买压,但动量指标为负且周跌 1.16%,市场谨慎。

两者均展现看涨结构,分析师认为可能接近关键吸筹阶段,或预示后续大幅上涨。

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Morning Post | Bitmine Plans to Raise $300 Million Through Preferred Stock Issuance; Polymarket Accuses Kalshi of Commercial Espionage

ChainCatcher's Daily Crypto Brief: Key developments from the past 24 hours include significant funding moves, regulatory actions, and market predictions. Bitmine announced a $300 million preferred stock fundraising. Polymarket accused rival prediction platform Kalshi of corporate espionage, citing numerous suspicious coincidences in product launches, a claim Kalshi strongly denied. The U.S. Department of Justice, in a joint "Disruption Week" anti-fraud operation with companies like Coinbase and Meta, froze over $3.8 million in cryptocurrency linked to scams. In infrastructure news, Macau completed its integration with the multi-central bank digital currency bridge, mBridge, aiming to build efficient cross-border payment channels. Cosmos Labs acquired the block explorer Mintscan. Market-wise, Geoffrey Kendrick, Standard Chartered's Head of Digital Assets Research, stated Bitcoin is nearing a bottom around $63,000, maintaining a year-end target of $100,000. He noted stability in U.S. spot Bitcoin ETF holdings. Ahead of SpaceX's anticipated IPO, internal insiders at Rocket Lab (RKLB) sold over $18.41 million in stock. In tokenization, Goldman Sachs partnered with Apex and Archax to launch a tokenized real estate fund. The meme token tracker GMGN reported the top trending tokens: on Ethereum, HEX, SHIB, LINK, PEPE, mUSD; on Solana, TROLL, swarms, WORLDCUP, neet, Buttcoin; and on Base, PEPE, toby, ODDS, ELSA, SKI.

链捕手4 min fa

Morning Post | Bitmine Plans to Raise $300 Million Through Preferred Stock Issuance; Polymarket Accuses Kalshi of Commercial Espionage

链捕手4 min fa

55TB to 28TB? The Rumor and Panic Behind Rubin's Memory Being Halved

Title: 55TB to 28TB? The Rumor and Panic Behind the Potential Halving of Rubin's Memory. On June 4th, a report from SemiAnalysis suggested NVIDIA's next-gen Vera Rubin NVL72 AI rack may ship with roughly 28TB of SOCAMM DRAM per rack instead of the anticipated 55TB, primarily using 96GB modules. This sparked a market panic, causing Micron's stock to drop over 10% on fears of halved memory demand. However, the article argues this panic is misguided for several key reasons. First, SOCAMM modules are socketed and upgradeable, not soldered. Lower initial configuration doesn't mean permanent demand loss. Second, the primary driver is a severe 2026 LPDDR5X supply shortage, not diminished need. NVIDIA is likely prioritizing rack shipments with available components. Third, with fixed total LPDDR5X supply, using less per rack could allow NVIDIA to ship *more* racks, not necessarily reducing overall memory orders. Micron's sharp drop was also attributed to a broader semiconductor sell-off triggered by Broadcom's earnings, with the SemiAnalysis report providing a convenient narrative for profit-taking after Micron's massive rally. In summary: the report on lower default configurations is likely accurate, but interpreting it as a demand collapse is wrong. The real risk for Micron lies in its reportedly minimal HBM4 share for Rubin, not in potentially flexible SOCAMM demand. The sell-off appears more like a correction amplified by coinciding negative catalysts.

marsbit21 min fa

55TB to 28TB? The Rumor and Panic Behind Rubin's Memory Being Halved

marsbit21 min fa

Exclusive from Yingke | Tang Wenbin's 'Yuanli Lingji' Merges with Logistics Robotics Company, and Secures Investment from Zhipu, SenseTime, Jieyue, and Others

Exclusive report: Embodied AI company "Yuanli Lingji" recently completed a new round of financing from major AI model firms including Zhipu AI, Stepfun, and SenseTime, alongside continued investments from industrial backers like Huaqin and SAIC Hengxu. Founded in March 2025 by Tang Wenbin, former co-founder and CTO of Megvii, Yuanli Lingji is a general-purpose embodied AI model company. In a notable move, the company has merged with logistics robotics firm "Atomix" (formerly known as Yuanli Juhe) through a share acquisition. Atomix, which originated from Megvii's logistics robotics business led by Tang in 2016 and was spun off in July 2024, has grown to become the world's second-largest supplier of pallet shuttle robots, with annual revenue nearing 1 billion RMB and over 500 projects globally for clients like Uniqlo and CATL. This merger aims to break the industry's "data deadlock" by combining Atomix's extensive real-world operational data from more than 20 countries with Yuanli Lingji's model training capabilities. The company's embodied AI model "DM0" utilizes a cross-domain training approach, integrating internet semantics, autonomous driving rules, and robotics data to achieve hardware-agnostic, precise manipulation even with a compact 2.4B parameter size. The collective investment from key AI players and the strategic merger signal a shift in the competitive landscape, as major model companies pivot from language tokens to physical actions ("from Token to Action"). The industry is entering a consolidation phase where hardware, AI models, data, and application scenarios converge to scale embodied intelligence, a trend mirrored by recent moves from giants like ByteDance and Skild AI.

marsbit29 min fa

Exclusive from Yingke | Tang Wenbin's 'Yuanli Lingji' Merges with Logistics Robotics Company, and Secures Investment from Zhipu, SenseTime, Jieyue, and Others

marsbit29 min fa

U.S. Stock Market Trends: Dow Hits New High, Nasdaq Falls, Whom Did Broadcom's Slap Wake Up?

U.S. Stocks Split: Dow Hits Record High as Nasdaq Slips; Broadcom's Plunge Sparks Rotation On June 4, the U.S. stock market saw a sharp divergence. The Dow Jones surged 875 points (+1.73%) to a record high of 51,561.93, while the Nasdaq Composite edged down 0.09%. The S&P 500 rose 0.41%. The primary catalyst was a sharp sell-off in AI-related chip stocks, led by Broadcom (AVGO). Despite reporting a 143% year-over-year jump in AI semiconductor revenue to $10.8 billion, the company's shares plunged about 14%. This was triggered by its maintained long-term AI revenue target, which failed to meet heightened expectations for a stock that had gained 55% this quarter and traded at a high P/E ratio. The slide dragged down the broader semiconductor sector and the technology板块. Conversely, money rotated into sectors like Healthcare (+3.14%), Financials (+2.67%), and Real Estate (+1.87%). UnitedHealth and Goldman Sachs were major contributors to the Dow's gains. The rotation was attributed to a search for value outside overheated tech names and a slight dip in Treasury yields. In other major news, SpaceX confirmed its IPO for June 12, targeting a record $75 billion raise at a ~$1.75 trillion valuation. Additionally, initial jobless claims rose to a four-month high, adding nuance to the labor market narrative ahead of the key May non-farm payrolls report. The day's action signaled that while the AI growth story remains intact, excessive valuations are prompting a market reassessment. Funds are moving, at least temporarily, from high-flying tech to more defensive and value-oriented sectors. The sustainability of this rotation hinges on upcoming economic data, particularly the jobs report, and the market's absorption of the massive SpaceX IPO.

marsbit32 min fa

U.S. Stock Market Trends: Dow Hits New High, Nasdaq Falls, Whom Did Broadcom's Slap Wake Up?

marsbit32 min fa

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

"Old Dogs" Become AI's New Darlings: Revaluing Legacy Infrastructure The AI investment narrative is shifting. Beyond the spotlight on core chipmakers like Nvidia, a new wave of interest is rising for legacy tech companies—Dell, HPE, Nokia, Cisco, Corning, Western Digital—once labeled as slow-growth, outdated stories. This resurgence stems from AI's evolution from model development to real-world deployment, creating massive demand for physical infrastructure. As AI moves into data center construction and enterprise adoption, the focus turns to who can actually build and deliver complex systems. These established players hold decades of experience in supply chains, integration, networking, and enterprise delivery—assets now critical for scaling AI. The revaluation can be grouped into three key infrastructure areas: 1. **Servers & Integration (e.g., Dell, HPE):** They are becoming essential system integrators, transforming GPUs into full-scale AI servers with networking, power, and cooling, then delivering them to clients. Strong recent earnings and AI-specific revenue/order growth for Dell and HPE underscore this shift. 2. **Networking & Connectivity (e.g., Corning, Nokia, Cisco):** As AI clusters grow, high-speed data transfer becomes paramount. Corning benefits from fiber demand for data center links, Nokia is exploring AI-integrated wireless networks (AI-RAN), and Cisco sees surging orders for data center switches—all critical for efficient AI operations. 3. **Storage (e.g., Western Digital, Seagate):** The AI data explosion requires vast capacity. Beyond high-speed memory (HBM), there's growing need for high-capacity HDDs to store training data, logs, video, and cold/archival data cost-effectively. This revaluation, however, is not a blanket endorsement. True reassessment requires concrete proof: AI-driven orders and revenue growth, upward revisions to company guidance, and sustainable improvements in profit quality, not just top-line sales. In essence, AI is not turning all old tech firms into high-growth stocks; it is selectively re-pricing the "old assets" of companies that are mission-critical for building the new AI infrastructure, transforming their legacy capabilities into renewed growth engines.

marsbit41 min fa

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

marsbit41 min fa

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