Bitcoin Smart Money: Glassnode Reveals How Large Traders Timed The Pullback

bitcoinist2025-10-09 tarihinde yayınlandı2025-10-09 tarihinde güncellendi

Özet

Data from Glassnode has revealed how the large Bitcoin traders showed expert timing in the derivatives market during the market...

Trusted Editorial content, reviewed by leading industry experts and seasoned editors. Ad Disclosure

Data from Glassnode has revealed how the large Bitcoin traders showed expert timing in the derivatives market during the market reversal.

Bitcoin Large Traders Have Shifted To A Net Short Bias

In a new post on X, on-chain analytics firm Glassnode has talked about how the large Bitcoin traders behaved during the latest pullback in the cryptocurrency’s price.

Below is the chart shared by Glassnode that shows the trend in the BTC Long/Short Bias, a metric tracking the difference between long and short positions opened by the large investors on derivatives exchanges, over the past couple of months.

Bitcoin Long/Short Bias

Looks like the value of the metric has plummeted in recent days | Source: Glassnode on X

From the graph, it’s visible that the Long/Short Bias has mostly been at a slight negative level for Bitcoin during the last few weeks, indicating that the large traders have just leaned toward short positioning. When BTC set its initial all-time high (ATH) above $125,000 on Saturday, however, the indicator assumed a small positive value, implying there was a slight bias toward a bullish sentiment among derivatives users.

Interestingly, this same behavior wasn’t seen during the second ATH break above $126,000 on Monday. In fact, the whales behaved in the completely opposite manner: the Long/Short Bias saw a plunge deep into the negative territory. “The shift to a net short bias suggests profit-taking on longs alongside new short positioning,” notes the analytics firm. Thus, it would seem that the large traders were anticipating a price pullback after the price top, so they started moving in advance.

The Long/Short Bias only saw a further decline when Tuesday’s fast crash below $121,000 took place. Now, the metric is sitting at a value of -4,416.20 BTC, which means bearish bets outweigh bullish ones by more than 4,400 tokens.

It now remains to be seen how sentiment among the Bitcoin whales will develop in the coming days. Another shift from smart money could potentially foreshadow another shift for the asset’s price as well, given the latest pattern.

In some other news, the recent Bitcoin price surge has meant that Percent Supply in Profit has broken into an extreme territory, as Glassnode has pointed out in another X post.

Bitcoin Percent Supply in Profit

The trend in the percentage of the BTC supply carrying an unrealized gain over the last few years | Source: Glassnode on X

As displayed in the above chart, the Bitcoin Percent Supply in Profit broke above 95% when it crossed the $117,000 level during the rally. Naturally, the metric later went on to reach 100% as BTC set a new ATH, since everyone is in the green whenever the cryptocurrency explores new price levels.

Historically, the metric being above 95% has often indicated overheated conditions for BTC. As the analytics firm explains, such a high value is “a hallmark of Euphoria phases, where widespread profitability often fuels accelerated profit-taking and rising market risk.”

BTC Price

Bitcoin has shown some recovery during the past day as its price has returned to the $123,000 mark.

Bitcoin Price Chart

The price of the coin seems to have overall moved sideways during the last five days | Source: BTCUSDT on TradingView
Featured image from Dall-E, Glassnode.com, chart from TradingView.com
Editorial Process for bitcoinist is centered on delivering thoroughly researched, accurate, and unbiased content. We uphold strict sourcing standards, and each page undergoes diligent review by our team of top technology experts and seasoned editors. This process ensures the integrity, relevance, and value of our content for our readers.

Keshav is a Physics graduate who has been employed as a writer with Bitcoinist since June 2021. He is passionate about writing and through the years, he has gained experience working in a variety of niches. Keshav holds an active interest in the cryptocurrency market, with on-chain analysis being an area he particularly likes to research and write about.

İlgili Okumalar

AI Bubble Warning: AI Investments Are Negative Returns for Most Tech Giants

The article issues a stark warning about a potential AI investment bubble. It notes that while the AI boom shares similarities with the TMT bubble of the late 1990s, its scale is vastly larger, currently driving 93% of U.S. GDP growth. Major hyperscale cloud providers like Microsoft, Alphabet, Amazon, Meta, and Oracle are planning to invest trillions in AI data centers over the coming years. However, calculations based on analyst projections for 2025-2030 reveal a concerning math problem: expected capital expenditure growth far outpaces projected revenue growth. Even under an extremely optimistic scenario of zero costs, the implied return on investment for most of these tech giants (except Amazon) is deeply negative. This suggests that the current trajectory could lead to one of history's largest shareholder value destruction events. The piece outlines two potential escapes: AI generating vastly more revenue than currently anticipated—a near-impossible task—or a significant cutback in the planned investment splurge. The latter scenario could trigger a domino effect, severely impacting the entire tech supply chain (from Nvidia to TSMC), potentially pushing the U.S. economy into recession, and causing a major stock market downturn. The author suggests upcoming high-profile IPOs by companies like OpenAI and Anthropic might represent a transfer of risk from early investors to public market participants. While the peak of the hype cycle might sustain investment through 2026, the fundamental financial dilemma remains unresolved, setting the stage for a potential market correction in 2027 or 2028, similar to the years following Alan Greenspan's "irrational exuberance" warning.

marsbit4 dk önce

AI Bubble Warning: AI Investments Are Negative Returns for Most Tech Giants

marsbit4 dk önce

From Tokens to Machine Labor: AI is Shifting from Tool to "Worker"

The article "From Token to Machine Labor: AI is Evolving from Tool to 'Worker'" argues that the business model for AI is shifting beyond simply selling computational resources (tokens, GPU hours) or model access. Instead, a new "machine labor market" is emerging, where the core economic transaction is the purchase of economically useful work directly performed by software. The central thesis is that AI pricing will evolve through four stages: 1) raw tokens, 2) standardized LLM capabilities (e.g., text generation), 3) industry-specific labor markets (e.g., legal review, radiology), and finally 4) a programmable results market where tasks like resolving a support ticket are bid on and priced based on outcome. In this future, buyers will care less about *which* model or GPU completes a task and more about whether the work meets specified standards for accuracy, latency, and cost. This transition reframes the impact of AI on human labor. Rather than simple replacement, it suggests a re-coordination where machines handle standardized, verifiable work, freeing humans for roles involving oversight, context management, responsibility, and final judgment. In some cases, this "last 1%" of human input becomes more valuable as it enables the other 99% to be automated. Furthermore, as AI reduces the cost of work, demand may expand, creating larger markets (e.g., 24/7 customer service) rather than just cheaper versions of existing ones. The article concludes that while infrastructure (GPUs, models, tokens) remains crucial upstream, the market is converging on a simpler, tradeable unit: machine labor that can be defined, measured, priced, and procured based on contractible specifications.

marsbit14 dk önce

From Tokens to Machine Labor: AI is Shifting from Tool to "Worker"

marsbit14 dk önce

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

The price of Xiaomi's MiMo-V2.5 series API has been permanently reduced by up to 99%, specifically for the "Input (Cache Hit)" cost, which covers users re-reading historical context in long conversations. MiMo's head, Luo Fuli, published a detailed technical blog to clarify that this drastic price cut stems from genuine engineering breakthroughs, not a marketing stunt or a simple price war. The core of the achievement lies in six key engineering optimizations. First, the model architecture adopts a Hybrid Sliding Window Attention (SWA), reducing the memory footprint (KVCache) to 1/7th of a traditional model. Second, a dual-pool memory management system actually utilizes these savings, allowing a single GPU to handle over 5 times more concurrent users. Third, an upgraded prefix caching mechanism achieves a cache hit rate of 93-95% for repeated reads, meaning most such requests bypass GPU computation entirely. Fourth, a self-developed distributed cache (GCache) utilizes idle SSD space on existing GPU servers, eliminating additional storage costs. Fifth, an intelligent scheduling system (LLM-Router) efficiently routes requests to maximize cache reuse and performance. Sixth, Multi-Token Prediction (MTP) accelerates the model's text generation ("output") side. Together, these systemic optimizations dramatically lower the real computational cost per request, enabling the 99% price reduction for cached inputs while reportedly maintaining positive gross margins. Luo Fuli's disclosure aims to shift the narrative from "price war" to a demonstration of substantive AI engineering progress.

marsbit2 saat önce

Xiaomi MiMo's 99% Price Cut is Not Marketing! Luo Fuli Posts on X to Refute Critics

marsbit2 saat önce

$26 Billion: An 'All-Chinese Team' Backs the World's Highest-Valued AI Programming Company

Cognition AI, the company behind the AI programmer "Devin," has raised over $1 billion in new funding at a valuation of $26 billion, just eight months after reaching a $10.2 billion valuation. The round was led by Lux Capital, General Catalyst, and 8VC. Founded by three young Chinese entrepreneurs with strong competitive programming backgrounds, Cognition initially gained fame with Devin, marketed as the world's first AI software engineer capable of handling tasks from start to finish. While its early demos were impressive, real-world usage revealed reliability and cost-effectiveness issues, leading to a significant price cut for Devin in 2025. A pivotal moment came when Cognition acquired the assets of AI IDE company Windsurf after a failed acquisition by OpenAI. This move gave Cognition a crucial developer-facing tool, allowing it to pursue a two-pronged strategy: Devin for autonomous task execution and Windsurf for integrated, collaborative coding within an IDE. This shift helped the company move away from the controversial "AI replacement" narrative towards a model of augmenting human engineers, particularly for repetitive or maintenance tasks. This strategic pivot is backed by strong commercial metrics. The company reports a 10x increase in enterprise usage this year, with an annual revenue run-rate of $492 million and a 50% month-over-month growth in enterprise Devin usage over the past six months. Its client list now includes major corporations like Goldman Sachs and Mercedes-Benz, as well as government agencies like NASA and the U.S. Army. Investors are betting on Cognition becoming a foundational piece of next-generation software engineering infrastructure, positioning it at the center of a hybrid future where AI agents and human developers work in tandem.

marsbit2 saat önce

$26 Billion: An 'All-Chinese Team' Backs the World's Highest-Valued AI Programming Company

marsbit2 saat önce

The Hottest 00s Generation on Wall Street

"Wall Street's Hottest '00s Phenom: The 25-Year-Old Fund Manager Who Bet on AI's 'Boring' Backbone" At just 25, Leopold Aschenbrenner, once fired by OpenAI, now runs a hedge fund worth $13.7 billion. His strategy? Betting against the consensus. While others chased AI chips, he invested early in the physical infrastructure powering the AI boom: electricity, data centers, and energy. Expelled from OpenAI's safety team in 2024, Aschenbrenner foresaw the coming bottleneck. He argued that AI progress would be limited not by algorithms, but by power, chip capacity, and space. Acting on this, he founded Situational Awareness LP to go long on these "old economy" assets. His bets have paid off spectacularly. His fund's assets soared from $255 million in late 2024 to $13.7 billion by Q1 2026. His portfolio is a direct reflection of his thesis: major long positions in fuel cell company Bloom Energy and data center/bitcoin mining firms like CleanSpark and Riot Platforms, which control critical land and power resources. Conversely, he holds massive put options against overheated semiconductor giants like NVIDIA and AMD. A notable exception was his bullish bet on storage company SanDisk, which surged ~160% in Q2. Aschenbrenner's vision is materializing. Tech giants like Amazon, Alphabet, and Meta are ramping up colossal capital expenditure on data centers. Global data center power consumption is projected to skyrocket, with AI accounting for over half by 2030. The demand for enabling technologies like optical fiber and modules is also exploding. His story underscores a fundamental truth of the AI era: the ethereal intelligence of algorithms rests on a very physical, heavy, and power-hungry foundation. The future is being built not just in code, but in concrete, copper, and kilowatts.

marsbit4 saat önce

The Hottest 00s Generation on Wall Street

marsbit4 saat önce

İşlemler

Spot
Futures
活动图片