Avalanche: Examining impact of $6M whale activity on AVAX prices

ambcryptoPublished on 2025-10-08Last updated on 2025-10-09

Key Takeaways 

Why is AVAX down?

Avalanche dropped by 5% in the past 24 hours, aligning with the correction seen in the crypto markets.

Can activity spark a reversal?

Rising on-chain activity suggested a potential rebound in price action.


Avalanche [AVAX] has recently drawn public attention, reflected in rising on-chain activity. However, its price dropped over 5% in the past 24 hours, at press time, extending to a 7% decline over the week.

This pullback aligns with the broader crypto market correction following last week’s bullish momentum. Notably, the dip attracted a significant buy-in, hinting at possible signs of a reversal.

Whales accumulate!

According to Arkham data, a whale bought about 200K AVAX valued at about $6 million in the past 24 hours. The activity indicated a classic accumulation behavior of informed money during periods of market strength.

At the same time, another whale transferred about $12 million into a Coinbase wallet.

avax avalanche

Source: Arkham

On top of that, activity on the blockchain was also on the rise.

Booming chain activity

On-chain data from DefiLlama revealed that the altcoin saw a $200 million increase in trading volume, as of writing, pushing its cumulative volume past $950 billion.

Decentralized exchange (DEX) activity made up nearly 33% of the total daily volume. Token liquidity stood at approximately $3.74 million, which included user rewards.

avax Avalanche

Source: DefiLlama

Development activity is continuously growing, which is contributing to the bullish sentiment.

The number of smart contracts on Avalanche’s ecosystem has more than tripled over the past year. As of press time, the cumulative number of contracts was more than 44 million.

The total burned AVAX reached 4.8 million, which reduces the supply. The average burn rate has been 1,250 tokens per day since mid-July.

More activity is expected as the Avalanche blockchain will be hosting FIFA’s NFT tokens for the 2026 World Cup using AvaCloud. As reported by CoinMarketCap, this would power real-world programs.

Will the altcoin reverse the weakening price?

On the charts, AVAX had broken below a narrowing rising wedge pattern. The altcoin confirmed the fall with an equal lower high at the breakout level.

On the four-hour chart, AVAX price was stabilizing around the 0.75 Fibonacci Retracement level. This was after breaking below the 200 Exponential Moving Average (EMA).

Reclaiming the 200 EMA as support would confirm the reversal. Still, if the current level held, it could be a great zone to go long as it aligned with the Fib level known to spark reversals.

Still, it was unclear.

avax Avalanche

Source: TradingView

Alternatively, AVAX could drop to $26 to retest the previously broken range high. Since mid-September, the altcoin has traded within a range between $22 and $26.

At present, AVAX is in a state of indecision, especially when viewed against the broader market backdrop. 

Still, both on-chain metrics and technical indicators are beginning to show early signs of a potential reversal.

Share

Related Reads

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.

marsbit15m ago

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

marsbit15m ago

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.

marsbit25m ago

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

marsbit25m ago

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.

marsbit2h ago

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

marsbit2h ago

$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.

marsbit2h ago

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

marsbit2h ago

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.

marsbit5h ago

The Hottest 00s Generation on Wall Street

marsbit5h ago

Trading

Spot
Futures

Hot Articles

How to Buy AVAX

Welcome to HTX.com! We've made purchasing Avalanche (AVAX) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Avalanche (AVAX) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Avalanche (AVAX)After purchasing your Avalanche (AVAX), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Avalanche (AVAX)Easily trade Avalanche (AVAX) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

8.0k Total ViewsPublished 2024.03.29Updated 2025.05.13

How to Buy AVAX

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 AVAX (AVAX) are presented below.

活动图片