XRP Breaks Down Yet Again, Losing the $2 Mark, with a Potential 10% Drop Looming?

金色财经Publicado a 2025-12-17Actualizado a 2025-12-17

Resumen

XRP has experienced a sharp decline, falling 4.3% in 24 hours and breaking below the critical $2 support level. The drop was driven by significant selling pressure, with $584 million in long liquidations and a doubling in trading volume to $3.9 billion. Despite the price drop, XRP ETFs have recorded 21 consecutive days of net inflows, indicating continued institutional interest. Key support is now at $1.86. A break below this level could lead to a further 10% decline toward the October 10 low of $1.58. The RSI is at 21.5, indicating extreme oversold conditions, which has previously led to minor rebounds. However, a sustained bounce depends on holding the $1.86 support. Investors are also exploring new opportunities like the presale of meme coin Maxi Doge ($MAXI), which has raised over $4 million. The current situation reflects a battle between institutional accumulation and retail selling. Caution is advised—wait for clear signs of a price bottom before considering entry.

XRP is really falling without any mercy! It plummeted 4.3% in 24 hours, breaking through the crucial $2 support level that had been holding for days. Selling pressure is maxed out, and the bulls look like they're about to give up~ Free group +Q:3260353596

Why such a steep drop? Turns out, $584 million fled overnight, long-term liquidation volumes surged, and many traders got caught completely off guard by this decline. The bulls were fighting hard to defend $2, but buying interest was pitifully low—forget a rebound, it was even hard to stabilize. Even more painful, yesterday's trading volume doubled, hitting $3.9 billion, and after the bears broke through, the selling pressure intensified!

But there's a strange contrast: even though the price is in the gutter, XRP's ETF has seen net inflows for 21 consecutive days! Institutions and long-term holders are quietly buying the dip, showing that big players in the regulated market still have confidence in it~

? Key Levels to Watch! A Break Below $1.86 Could Mean Another 10% Drop?

Looking at the 4-hour chart, after breaking below $2, the focus is squarely on the $1.86 support level. The bulls have no choice but to defend this line now—if it fails, the next stop could be the October 10 low of $1.58, which would mean another 10% drop in the short term. Just thinking about it hurts!

A small silver lining: the RSI has now dropped to 21.5, indicating extreme oversold conditions. The previous two times it hit this level, the price bounced back slightly, so maybe there's a chance for a small dip-buying opportunity this time? But that depends entirely on holding $1.86; otherwise, it's all for nothing.

Also, many crypto investors are starting to shift to new opportunities, like the presale meme coin Maxi Doge ($MAXI), which has already raised over $4 million. Some analysts say it resembles the early days of Dogecoin, so those interested might want to keep an eye on it~

To sum up: XRP is currently a tug-of-war between "institutions buying the dip vs. retail selling." The key is whether $1.86 can hold. Don't blindly buy the dip—wait for clear signs of stabilization before jumping in, or you might get burned again! Free group +Q:3260353596

Lecturas Relacionadas

Huang Renxun Dramatically 'Saves' South Korean Stock Market

In early June, South Korea's stock market experienced a sharp decline, with the KOSPI index dropping over 5% and triggering a trading halt. Amid this volatility, NVIDIA CEO Jensen Huang's visit to Seoul provided a dramatic boost to market sentiment. During his trip, Huang held a dinner meeting with SK Group Chairman Chey Tae-won and SK Hynix CEO Kwak Noh-Jung. He announced that NVIDIA's new Vera CPU would utilize SK Hynix DRAM and confirmed a multi-year technical collaboration between the two companies. This partnership aims to co-develop next-generation memory for NVIDIA's AI infrastructure roadmap, covering products from data center supercomputers to personal AI devices. Huang also publicly commented that AI company stocks were attractively priced. A key announcement was that NVIDIA's upcoming Vera Rubin AI supercomputer systems will use HBM4 memory, with supply qualifications granted to all three major suppliers: SK Hynix, Samsung Electronics, and Micron Technology. Despite this multi-sourcing strategy, Huang warned that the industry-wide chip shortage, affecting everything from wafers to packaging, is expected to persist for several years due to relentless demand from global AI factory construction. The collaboration extends beyond memory supply. SK Hynix will employ NVIDIA's AI platforms and Omniverse digital twin technology to enhance its own semiconductor design, simulation, and manufacturing processes, aiming for more autonomous factory operations. This visit builds upon a prior October 2025 agreement for SK Group to build a large-scale AI data center using over 50,000 NVIDIA GPUs. Huang's itinerary also included meetings with other Korean giants like Hyundai, LG, and Samsung, indicating NVIDIA's broader strategy to deepen ties with South Korea's tech industry.

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Huang Renxun Dramatically 'Saves' South Korean Stock Market

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When Inference Becomes a Scarce Resource, Who Captures the Value?

When Inference Becomes the Scarce Resource, Who Captures the Value? The core AI bottleneck has shifted from model training to inference (runtime execution). While concerns persisted about an "AI compute gap"—initially a $200B, now a $600B problem—the market is now recognizing that the solution and value lie in the inference layer. Nvidia's financial restructuring around "serving tokens" and Cerebras's successful IPO highlight this shift. Inference is a recurring, usage-based cost, estimated to be 10-50x larger than the one-time training market, especially with the rise of agentic AI. The inference stack spans six layers: silicon (e.g., Nvidia), bare metal (e.g., CoreWeave), GPU rental/aggregation, deployment/optimization, model APIs, and end applications. Most companies operate in one layer. However, Hyperbolic uniquely spans three layers (GPU rental, deployment, and model APIs) without owning any hardware. It aggregates fragmented GPU supply from multiple cloud providers into a standardized pool, offering developers the cheapest available compute through intelligent routing. Its multi-cloud aggregation creates a data moat and a flywheel: more supply leads to better pricing data and liquidity, attracting more developers and providers. In contrast, applications like Venice operate at the top of the stack, reselling privacy-wrapped inference but remaining dependent on and constrained by the underlying compute costs they purchase. As inference demand explodes, value accrues not just to consumer applications but increasingly to the aggregation and routing layer that captures their cost of revenue. The coming potential GPU oversupply reinforces this dynamic. While hardware owners may suffer from depreciation, asset-light aggregators like Hyperbolic benefit from price arbitrage, routing workloads to the cheapest available capacity. The ultimate winner in the inference economy may not be the entity with the most GPUs, but the one that can most efficiently discover, aggregate, and route the world's fragmented compute.

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When Inference Becomes a Scarce Resource, Who Captures the Value?

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