Ethereum Whales Loses Nearly 25% Of Their Holdings Amid Market Shift

bitcoinistPublished on 2026-05-09Last updated on 2026-05-09

Abstract

Ethereum whales, defined as addresses holding between 1,000 and 10,000 ETH, have sharply reduced their holdings by approximately 21.5% (from 15.95 million to 12.52 million ETH) between October 2025 and May 2026. This sell-off, flagged as a supply overhang by analyst Ali Charts, indicates fading bullish sentiment among major investors and raises questions about short-term market stability. It contrasts with a previous accumulation phase and recent buying sprees, suggesting Ethereum's price may struggle to reach $3,000 without new institutional or retail demand. Concurrently, Ethereum's utility is growing, with tokenized U.S. treasuries on its network surpassing $8 billion, highlighting its role in traditional finance despite current price struggles below $2,300.

With the crypto market turning slightly bearish, the Ethereum price has lost the $2,300 mark, raising questions about the stability of its recent upswing. Amid this sideways price action, a report shows that a fading bullish sentiment among Ethereum whales is evidenced by a significant decline in their holdings.

Large ETH Players’ Portfolio Shrinks Sharply

After examining Ethereum whales‘ holdings, Ali Charts, a seasoned market expert and trader, revealed that these key investors are exhibiting a trend not seen in over a year. While ETH’s price is slowly losing its upside momentum, a major wave of selling has rattled the ETH market.

This heightened selling activity was observed among large investors or whales holding between 1,000 ETH and 10,000 ETH as they dump nearly a quarter of their holdings in the face of uncertainty. Such a trend underscores a major decrease in exposure, which raises questions about confidence and short-term market stability.

Since October 6, 2025, Ethereum holders between 1,000 and 10,000 ETH have undergone a notable regime shift in their market activity. Prior to the shift, the cohort was spotted in a steady accumulation phase. During the period, these investors’ ETH portfolio saw a rise from 12.95 million ETH in April 2025 to a peak of 15.95 million ETH by October 6, 2025. Fast forward to May 2026, and this behavior has flipped again.

Source: Chart from Ali Charts on X

As seen in the chart shared by Ali Charts, the amount of ETH held by these mid-tier whales has dropped from 15.95 million to about 12.52 million, which represents an approximately 21.5% decrease in their total position. This simply implies a dramatic change in positioning from some of the network’s largest investors.

Ali Charts have flagged this development as a supply overhang. According to the expert, this suggests that the road to the $3,000 may require a fresh wave of demand from institutional or retail investors to offset whale distribution.

It is worth noting that a few days ago, ETH whales went on a buying spree. During the period, over 140,000 ETH, valued at around $322 million, were scooped up by these key players. When high-net-worth holders are buying more, it is a sign that smart money is positioning for a breakout.

Tokenized Treasuries Surges On The ETH Network

Even with the Ethereum price still significantly down from its all-time high, this drop has not hindered institutional adoption, which is currently accelerating. Coin Bureau has reported a surge in tokenized treasuries across the leading network.

The chart shows that the ETH network just surpassed $8 billion in tokenized US treasuries for the first time in its history. The rise in blockchain-based sovereign debt instruments underscores Ethereum’s growing relevance as a foundation for actual financial assets.

In addition, the week experienced the expansion of Stripe’s BRIDGE stablecoins to Celo and plans for Canada’s first regulated stablecoin on Ethereum. Despite the growth, ETH’s price continues to struggle to break key short-term resistance.

ETH trading at $2,279 on the 1D chart | Source: ETHUSDT on Tradingview.com

Related Questions

QAccording to the article, what has happened to the holdings of Ethereum whales in the range of 1,000 to 10,000 ETH?

ATheir holdings have dropped sharply, decreasing by approximately 21.5% from 15.95 million ETH in October 2025 to about 12.52 million ETH by May 2026.

QWhat does market expert Ali Charts suggest is needed for Ethereum's price to reach $3,000?

AAli Charts suggests that reaching $3,000 may require a fresh wave of demand from institutional or retail investors to offset the distribution pressure from whale selling.

QWhat positive development regarding institutional adoption is reported on the Ethereum network despite the price drop?

ATokenized US treasuries on the Ethereum network have surged, surpassing $8 billion for the first time in its history, indicating growing institutional adoption for real financial assets.

QHow did the behavior of the 1,000-10,000 ETH whale cohort change in early October 2025?

ATheir behavior shifted from a steady accumulation phase, where holdings grew from 12.95 million ETH in April to a peak of 15.95 million ETH, to a significant selling phase starting around October 6, 2025.

QWhat was the approximate value and amount of ETH that whales reportedly bought in a recent buying spree mentioned in the article?

ADuring the recent buying spree, whales scooped up over 140,000 ETH, which was valued at around $322 million at the time.

Related Reads

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit11h ago

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit11h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit13h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit13h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit13h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit13h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片