Solana dips below $120 as activity cools – Yet THIS group leans in, why?

ambcryptoPublished on 2025-12-20Last updated on 2025-12-20

Abstract

Despite short-term volatility and declining activity metrics, Solana (SOL) demonstrated resilience as its price dipped below $120. While retail participation waned amid market fear, on-chain data revealed significant whale accumulation during the price weakness. A specific wallet purchased 41,000 SOL worth $5 million, following a historical pattern of profitable accumulation. Furthermore, Solana ETFs recorded $11 million in net inflows, indicating sustained institutional demand that counterbalanced spot selling pressure. Technically, SOL found support between $117-$122, with improving momentum indicators suggesting a potential reversal. The price action underscores a divergence between short-term fear and long-term conviction, with strategic investors showing confidence during the downturn.

Strong networks continued attracting capital despite short-term volatility across digital asset markets, even as some chain activity weakened and key support levels gave way.

Market fear reduced retail participation across crypto, pressuring usage metrics without erasing long-term network relevance. Solana remained one of the more resilient Layer-1 chains as risk appetite deteriorated.

Solana’s [SOL] network Revenue peaked sharply in January before declining to the lowest levels of the year.

The pullback erased earlier gains as trading activity slowed across decentralized applications. That contraction aligned with extreme fear conditions rather than signs of structural deterioration.

Weekly Active Addresses also trended lower during the same period. The decline reflected risk-off behavior and reduced retail participation across crypto markets.

Activity stabilized near recent lows as volatility compressed.

Solana whale accumulation emerges below $120

As Solana dropped back below $120 on the 18th of December, whale accumulation intensified across several wallets.

Wallet G6gemN bought 41,000 SOL worth approximately $5 million during the dip. The buying suggested strategic positioning into weakness rather than reactive selling.

Historical behavior added context to the move.

About eight months earlier, the same wallet accumulated 24,528 SOL near $122. It was later sold for around $175, realizing roughly $1.28 million in profit.

The renewed accumulation followed a familiar pattern. Price weakness attracted capital instead of triggering broad distribution. Whale behavior pointed toward confidence during periods of elevated fear.

SOL ETF inflows offset spot selling pressure

Spot Solana ETFs recorded $11 million in Net Inflows on the 18th of December. Institutional products continued absorbing supply even as spot prices weakened.

ETF demand counterbalanced selling pressure during the pullback.

Flows suggested positioning during fear-driven declines. Institutions appeared willing to accumulate amid heightened volatility. ETF activity reinforced demand beneath short-term weakness.

Support holds as momentum steadies

From a technical perspective, Solana traded near $124 at press time, after dipping from $122 to $117.

Bulls defended that zone, pushing price back into the broader $122–$145 accumulation range. Price action held around support, signaling absorption rather than continuation lower.

Momentum indicators also improved. MACD showed a developing bullish crossover, while RSI printed a bullish divergence as selling pressure faded near recent lows. Momentum improved as Solana remained within its established accumulation range.

That setup left traders focused on whether support could hold as broader sentiment stabilized.


Final Thoughts

  • Solana’s recent price action highlighted a growing divide between short-term participation and longer-term conviction.
  • While fear weighed on activity metrics, accumulation beneath support hinted at confidence during uncertainty.

Trending Cryptos

Related Questions

QWhat was the key price level that triggered increased whale accumulation for Solana?

AThe key price level that triggered increased whale accumulation was below $120, specifically on the 18th of December.

QHow did Solana ETF flows behave during the market dip and what was their significance?

ASolana ETFs recorded $11 million in net inflows on December 18th, which helped counterbalance spot selling pressure and indicated institutional accumulation during the fear-driven decline.

QWhat technical indicators showed improvement for Solana's price momentum near the support level?

AThe MACD showed a developing bullish crossover and the RSI printed a bullish divergence, indicating improving momentum as selling pressure faded near recent lows.

QHow did the activity on the Solana network, such as Weekly Active Addresses and Revenue, change during this period?

ASolana's network revenue declined to its lowest levels of the year, and Weekly Active Addresses also trended lower, reflecting reduced retail participation and risk-off behavior in the crypto markets.

QWhat does the behavior of 'Wallet G6gemN' suggest about large investors' strategy during the price dip?

AThe behavior of Wallet G6gemN, which bought 41,000 SOL during the dip, suggests a strategy of strategic positioning into weakness and accumulation during periods of elevated fear, rather than reactive selling.

Related Reads

IPO Imminent, OpenAI Faces Major Personnel Upheaval

OpenAI, preparing for a potential IPO, is experiencing significant leadership turmoil. In mid-August 2026, longtime "GPU geek" Scott Gray quietly left, and within three days, Chief Operating Officer Brad Lightcap (8-year veteran) and Chief Revenue Officer Denise Dresser (8-month tenure) departed. This follows a broader exodus of at least 10 senior executives in 2026, including heads of product, safety, and ethics. Analysts view this as a strategic "surgery" to transform from a research lab into a sales-driven enterprise company before going public. Revenue now tilts toward enterprise clients, surpassing consumer income sooner than expected, with annualized revenue reaching $40 billion. The new CRO, Dali Rajic, is a veteran enterprise sales leader. Concurrently, OpenAI has disbanded independent safety teams like "Preparedness," which assessed catastrophic risks, integrating their functions into core research. Critics warn this removes dedicated "brakes" on AI development. The leadership vacuum raises questions about who is the clear second-in-command after former apps CEO Fidji Simo moved to an advisory role. Co-founder Greg Brockman appears to be consolidating power. As OpenAI races against rival Anthropic ($47B annualized revenue), it faces the dual challenge of commercial execution while managing the departure of foundational technical talent and ensuring responsible AI development remains a priority.

marsbit48m ago

IPO Imminent, OpenAI Faces Major Personnel Upheaval

marsbit48m ago

AI Can 'Have Moods Too'! New Research from USTC: Confusion and Anxiety Make AI Work Better

The article discusses research from the University of Science and Technology of China and Oxford, revealing that allowing AI to recognize and act upon simulated "internal emotions" can significantly improve its performance. The study demonstrates a coherent pairing between specific emotional states in AI agents and their subsequent skill choices. For instance, an agent feeling curious and desirous will search for products, while one feeling confused and tense will rephrase queries. This mirrors human decision-making influenced by emotions. Statistical validation showed a 76.5% semantic consistency in these pairings. Crucially, the research challenges the traditional view of AI errors as flaws to be eliminated. It found that "bad" emotions like confusion, tension, or frustration serve as useful metacognitive signals, indicating a mismatch between the current strategy and the environment. By responding to these signals, AI can proactively adjust before a failure occurs. This is particularly effective in complex tasks prone to failure. For example, in tasks like "heating an item" and "picking up two items," success rates surged from 9.6% to 56.9% and 4.4% to 31.3%, respectively, when using the emotion-driven skill selection method (EMOTION2SKILL). The AI's "nervous" state about a closed microwave, for instance, prompted it to check and open it first, preventing failure. The article also mentions related work from Tianjin University, which embeds emotional prediction into world models (Large Emotional World Model, LEWM), significantly improving prediction accuracy in human-centric environments. Removing emotional data was found to degrade performance even in unrelated logical reasoning tasks. These studies build on earlier findings, like those from Anthropic, that identifiable emotional representations exist within large language models (LLMs). The focus is shifting from philosophical debate about AI emotion to practically harnessing these internal states as functional signals to enhance AI robustness and capability.

marsbit1h ago

AI Can 'Have Moods Too'! New Research from USTC: Confusion and Anxiety Make AI Work Better

marsbit1h ago

Trading

Spot

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 SOL (SOL) are presented below.

活动图片