Goldman Sachs Embraces Crypto: Votes Confidence in ETH with $2.3 Billion Allocation

marsbitPublished on 2026-02-11Last updated on 2026-02-11

Abstract

Goldman Sachs has allocated $2.361 billion in cryptocurrency exposure through ETFs as of Q4 2025, representing about 0.3% of its total $811 billion portfolio. Despite a market-wide pullback that led to a 39.4% reduction in Bitcoin ETF holdings and a 27.2% cut in Ethereum ETF positions, the bank maintained nearly equal exposure to both—$1.06 billion in Bitcoin and $1 billion in Ethereum—even though Bitcoin's market cap is 5.7 times larger. This near-equal weighting signals a strategic vote of confidence in Ethereum, which Goldman views as a core infrastructure asset with strong network effects and application potential, contrasting with Bitcoin’s role as a macro hedge. The bank also initiated smaller positions in XRP and Solana ETFs. Goldman’s approach reflects a cautious, compliance-first strategy, emphasizing liquidity and institutional acceptance. Its evolving stance—from skepticism in 2020 to active engagement—mirrors a broader Wall Street trend of gradual adoption driven by client demand and regulatory clarity. The report notes that institutional adoption is a slow process, with major capital inflows potentially taking years to materialize fully.

Author: Nancy, PANews

Today, it is no longer news for Wall Street giants to enter the crypto space. In crypto sectors such as ETFs, RWA, and derivatives, the presence of mainstream institutions is becoming increasingly clear. What the market truly cares about has long moved from whether to enter to how to position.

Recently, Goldman Sachs disclosed its crypto allocation of up to $2.3 billion. Although this is still a "small position" in its overall asset landscape and has significantly reduced compared to before, its holding structure is quite meaningful. Despite the vast difference in market capitalization, Goldman Sachs maintains nearly equal exposure to BTC and ETH.

This detail may be more significant than the size of the holdings itself.

On Equal Footing with BTC, Goldman Sachs Casts a Vote of Confidence in ETH

At a time when Ethereum's price continues to face pressure and market sentiment has noticeably cooled, Goldman Sachs' latest disclosed holding structure sends a signal different from market sentiment.

According to the 13F filing, as of Q4 2025, Goldman Sachs indirectly holds approximately $2.361 billion in crypto assets through ETFs.

In the context of its overall portfolio, this allocation is not prominent. Goldman Sachs' total investment portfolio size in the same period was as high as $811.1 billion, with crypto asset exposure accounting for only about 0.3%. For traditional financial giants managing trillions of dollars, such a proportion can only be described as a trial. In the eyes of mainstream players, crypto remains an alternative asset, not a core allocation. Small-scale participation can meet client demands, maintain market participation, and strictly control risks in a volatile environment.

What is truly noteworthy is not the size, but the holding structure and direction.

In the fourth quarter of last year, the crypto market overall corrected, and spot ETF products also saw large net outflows. Goldman Sachs also reduced its positions accordingly, with Bitcoin spot ETF and Ethereum spot ETF holdings decreasing by 39.4% and 27.2% quarter-on-quarter, respectively. At the same time, it newly established positions in XRP ETF and Solana ETF in the quarter, beginning to dabble in second-tier assets.

By the end of the quarter, Goldman Sachs held approximately 21.2 million shares of spot Bitcoin ETF, with a market value of about $1.06 billion; held approximately 40.7 million shares of spot Ethereum ETF, with a market value of about $1 billion; and allocated about $152 million to XRP ETF and $109 million to Solana ETF.

In other words, nearly 90% of crypto exposure is still concentrated in the two core assets, BTC and ETH. Compared to some aggressive asset managers or crypto-native funds, Goldman Sachs' strategy is clearly偏向稳健, with liquidity, compliance, and institutional acceptance remaining its priority allocation logic.

But more significant is the nearly equal weighting of BTC and ETH.

Currently, Bitcoin's market capitalization is about 5.7 times that of Ethereum, yet Goldman Sachs did not allocate based on market cap weighting but instead placed ETH on essentially equal footing with BTC. This means that within its asset framework, Ethereum has been elevated to a second strategic-level crypto asset. Moreover, during the position reduction in Q4 2025, the reduction in ETH positions was 12% less than that of BTC positions. To some extent, this is an over-allocation vote of confidence.

This preference is not a temporary move.

Over the past few years, Goldman Sachs has continuously布局 around asset tokenization, derivative structure design, infrastructure, and OTC trading, most of which are highly related to the Ethereum ecosystem.

In fact, several years ago, Goldman Sachs' research department publicly predicted that ETH's market capitalization could potentially surpass BTC in the coming years, citing its network effects and ecological application advantages as a native smart contract platform.

This judgment continues to this day. In the "Global Macro Research" report released last year, Goldman Sachs再次强调 that from dimensions such as real utility, user base, and technological iteration speed, Ethereum has the potential to become the core carrier of mainstream crypto assets.

Although Ethereum has recently shown a divergence between price and fundamentals, Goldman Sachs maintains a relatively positive judgment. It pointed out that Ethereum's on-chain activity paints a different picture, with the number of new daily addresses reaching 427,000 in January, a record high, far exceeding the average of 162,000 addresses per day during the DeFi Summer of 2020. Meanwhile, the number of daily active addresses reached 1.2 million, also setting a historical record.

Perhaps, in the asset logic of Wall Street institutions, Bitcoin has become a macro hedging tool, while Ethereum carries the structural narrative of on-chain finance and application ecology. The two represent different dimensions of allocation logic: the former偏向 value storage, the latter betting on infrastructure and network effects.

Goldman's Turnaround, Wall Street's Hesitation and Entry

Goldman Sachs is also a "late" crypto player.

If the timeline is extended, this typical traditional financial institution's entry path has not been激进, adopting a "compliance first, gradual trial" approach.

As early as 2015, Goldman Sachs filed a patent application for a securities settlement system based on SETLcoin, attempting to explore using类区块链 technology to optimize the clearing process. At that time, Bitcoin had not yet entered the mainstream view, and this was more of a technical interest rather than asset-level recognition.

In 2017, when Bitcoin's price soared to a historical high, Goldman Sachs一度 planned to set up a crypto trading desk to provide Bitcoin-related services; in 2018, it hired former crypto traders to prepare a Bitcoin trading platform. At that time, Goldman Sachs had already begun to正面接触 this emerging market.

But the real attitude shift occurred in 2020. That year, Goldman Sachs explicitly stated in a client conference call that Bitcoin could not even be considered an asset class, as it neither generates cash flow nor effectively hedges inflation. This public bearishness sparked considerable market controversy.

Goldman Sachs began including Bitcoin in its weekly asset class reports in 2021

A year later, Goldman Sachs' stance quickly softened. In 2021, against the backdrop of rising institutional client demand, Goldman Sachs restarted its cryptocurrency trading department, began trading Bitcoin-related derivatives, and partnered with Galaxy Digital to launch Bitcoin futures trading products. In 2022, Goldman Sachs completed its first crypto OTC transaction and expanded its digital asset team. By 2024, it not only invested in several crypto companies but also formally entered the crypto spot ETF market.

The true comprehensive acceptance occurred in the last two years.

In March 2025, Goldman Sachs首次 mentioned cryptocurrency in its annual shareholder letter, acknowledging intensified industry competition and judging that regulatory clarity would drive a new wave of institutional adoption, with areas such as tokenization, DeFi, and stablecoins expected to grow under new regulations. More recently, its CEO David Solomon publicly confirmed that it is increasing research and investment in tokenization, stablecoins, and prediction markets.

This转变剧本 is not uncommon among traditional old money.

For example, in 2025, Skybridge Capital founder Anthony Scaramucci admitted that although he had接触 Bitcoin as early as 2012, it took him a full eight years to make his first Bitcoin investment because he initially did not understand it and was full of doubts. It wasn't until he真正研究 blockchain and Bitcoin mechanisms that he realized it was a "great technological breakthrough." He even stated that 90% of people would lean towards Bitcoin if they "did some homework."

Today, Skybridge Capital holds a significant amount of Bitcoin and invests about 40% of client funds in digital assets. Amid the recent bearish sentiment, Scaramucci revealed that the institution has been building Bitcoin positions in batches at $84,000, $63,000, and the current range, describing buying Bitcoin in a downward trend as "catching a falling knife" but remains firmly long-term bullish.

These elite Wall Street investors always prioritize risk at the core of their decisions, typically choosing to allocate on a规模化 scale only when risks are controllable.

Moreover, the decision-making cycle of institutions determines that真正的资金入场 is a marathon.

According to Bitwise Chief Investment Officer Matt Hougan in a recent interview, the next batch of potential buyers仍然是 financial advisors, large brokerages like Morgan Stanley, family offices, insurance companies, and sovereign nations. Bitwise's average client requires 8 meetings before allocating assets. We typically meet quarterly, so "8 meetings" means a decision cycle of up to 2 years. Morgan Stanley only approved Bitcoin ETFs in Q4 2025; their "8-meeting alarm clock" has just started, and真正的资金流入 may not爆发 until 2027. This is similar to the situation when gold ETFs were launched in 2004; inflows increased year by year, taking a full 8 years to reach the first peak. Most professionally managed money does not currently hold Bitcoin.

The journey of crypto assets from边缘资产 to mainstream assets is itself a slow and曲折 process. When former bears start holding in compliant ways, when skeptics turn into long-term allocators, the real change in the crypto market may not be in the行情, but in the upgrade of participant structure.

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit46m ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit46m ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit51m ago

Token Inefficient, Economy Tokenless

marsbit51m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit56m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit56m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit57m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit57m ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h 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

Top Questions

Hot Categoriesright-arrow

Hot Tagsright-arrow