Crypto

Decentralized cryptocurrency exchanges (DEXs) continue to challenge the dominance of centralized platforms, even as a recent $6.2 million exploit on Hyperliquid highlights risks in DEX infrastructure.

A cryptocurrency whale made at least $6.26 million profit on the Jelly my Jelly (JELLY) memecoin by exploiting the liquidation parameters on Hyperliquid, Cointelegraph reported on March 27. 

The exploit was the second major incident on the platform in March, noted CoinGecko co-founder Bobby Ong.

“$JELLYJELLY was the more notable attack where we saw Binance and OKX listing perps, drawing accusations of coordinating an attack against Hyperliquid,” Ong said in an April 3 X post, adding:

“It’s clear that CEXes are feeling threatened by DEXes, and are not going to see their market share erode without putting on a fight.”

DEX growth reshapes derivatives market

Hyperliquid is the eighth-largest perpetual futures exchange by volume across both centralized and decentralized exchanges. This puts it “ahead of some notable OGs such as HTX, Kraken and BitMEX,” Ong noted, citing an April 4 research report.

Related: Bitcoin to $110K next, Hyperliquid whale bags $6.2M ‘short’ exploit: Finance Redefined

Hyperliquid’s growing trading volume is starting to cut into the market share of other centralized exchanges.

Hyperliquid is the 12th-largest derivatives exchange, with an over $3 billion 24-hour open interest — though it still trails Binance’s $19.5 billion by a wide margin, CoinGecko data shows.

According to Bitget Research analyst Ryan Lee, the incident may harm user confidence in emerging decentralized platforms, especially if actions taken post-exploit appear overly centralized.

“Hyperliquid’s intervention — criticized as centralized despite its decentralized ethos — may make investors wary of similar platforms,” Lee said.

Whale exploits Hyperliquid’s trading logic

The unknown Hyperliquid whale managed to exploit Hyperliquid’s liquidation parameters by deploying millions of dollars worth of trading positions.

The whale opened two long positions of $2.15 million and $1.9 million, and a $4.1 million short position that effectively offset the longs, according to a postmortem by blockchain analytics firm Arkham.

When the price of JELLY rose by 400%, the $4 million short position wasn’t immediately liquidated due to its size. Instead, it was absorbed into the Hyperliquidity Provider Vault (HLP), which is designed to liquidate large positions.

Related: Polymarket faces scrutiny over $7M Ukraine mineral deal bet

As of March 27, the unknown whale still held 10% of the memecoin’s total supply, worth nearly $2 million, despite Hyperliquid freezing and delisting the memecoin, citing “evidence of suspicious market activity” involving trading instruments.

The Hyperliquid exploit occurred two weeks after a Wolf of Wall Street-inspired memecoin — launched by the Official Melania Meme (MELANIA) and Libra (LIBRA) token co-creator Hayden Davis — crashed over 99% after launching with an 80% insider supply.

Magazine: Memecoins are ded — But Solana ‘100x better’ despite revenue plunge

Key takeaways

• Grok 3 adjusts its predictions based on evolving market trends by analyzing real-time data patterns.

• Combining technical analysis with sentiment data improves accuracy; Grok 3 effectively identifies potential trade opportunities.

• Backtesting strategies before live trading is crucial; testing Grok 3’s prompts using historical data helps refine conditions and improve performance.

• While Grok 3 can automate trades, human oversight remains critical in adapting to unexpected market conditions.

Crypto trading is complex. Prices can swing wildly, and even experienced traders struggle to keep up. That’s why automation tools are gaining attention, with many now exploring Grok 3, an advanced artificial intelligence (AI) model from xAI (founded by Elon Musk).

Grok 3 wasn’t built specifically for trading, but its ability to analyze data, spot patterns and interpret trends has encouraged traders to test it for automated strategies. The idea is simple: Let Grok 3 make data-driven decisions, removing the emotional guesswork that often leads to poor trades.

But does it actually work? Some traders report impressive results, while others find it unpredictable, especially in volatile markets.

This article digs into what happens when you automate crypto trades with Grok 3. From successful strategies to unexpected risks, you’ll get a clear picture of what to expect, plus actionable tips to improve your results.

What is Grok 3 and how does it relate to crypto trading?

Grok 3 is an AI model designed by xAI, an artificial intelligence company founded by Elon Musk. While its primary focus is natural language processing, some traders are now testing Grok 3 as a potential tool for improving crypto trading strategies. Unlike traditional trading bots operating on rigid rules, Grok 3’s flexible design allows it to analyze diverse data sources and uncover patterns that might be overlooked.

Why some traders are turning to Grok 3

Grok 3’s appeal lies in its ability to handle complex data, a crucial advantage in crypto markets, where price moves are often triggered by unexpected events or sentiment shifts.

Here’s where traders say Grok 3 has potential:

• Identifying market sentiment trends: Crypto markets are heavily influenced by emotions like FOMO (fear of missing out) and FUD (fear, uncertainty, doubt). Grok 3 can analyze social media, news headlines and community discussions to assess changing sentiment, a key factor in crypto volatility.

• Recognizing hidden patterns: Grok 3’s machine learning capabilities allow it to detect subtle correlations between indicators that traditional bots may overlook. For instance, Grok 3 may link an increase in social sentiment with rising whale activity to predict bullish momentum.

• Flexible analysis based on prompts: Rather than following static rules like “Buy when RSI falls below 30,” Grok 3 enables traders to design more complex strategies using natural language instructions.

What happens when Grok 3 is used to automate crypto trades?

Grok 3 isn’t your typical crypto trading bot. It doesn’t place trades directly or integrate with exchanges on its own. But it can help traders build smarter, faster and more flexible automation systems. From writing trade logic to analyzing market sentiment, Grok 3 is already being used in the real world to streamline how crypto strategies are created and tested.

Instead of manually scripting every piece of logic, traders are now using Grok 3 to generate working code for bots. For example, a user asked Grok 3 to write token buy/sell logic with parameters like slippage, take-profit and gas priority fees. It generated a script that can be plugged into DeFi tools or expanded with 0x and Uniswap APIs.

Some traders use Grok 3 to build end-to-end bots tailored to niche tokens or specific strategies. In another example, Grok 3 was used to create an automated system that scans price action and triggers trades under strict conditions. It doesn’t just stop at buy/sell logic. Grok also writes portfolio rebalancing scripts and can simulate how positions would perform under different volatility conditions.

Here is an example of a prompt fed into Grok 3, along with the output received.

Grok 3’s response: High-frequency trading bot framework for Solana (SOL)

Below is a structured outline for a high-frequency trading bot framework designed for Solana (SOL), focusing on one-minute price fluctuations, risk management and trade execution. This outline provides a modular structure with placeholders for key components, avoiding specific implementation details as requested.

1. Core configuration

• Purpose: Define global settings and constants for the bot.

• Components:

  Solana network endpoint (e.g., mainnet RPC URL)

  Wallet configuration (private key or keypair for trading)

  Trading pair (e.g., SOL/USDC)

  Timeframe (one-minute candlestick data)

  Trade size ($100 per position)

  Max trades (10 concurrent or sequential positions)

  Profit target ($50 total)

  Max loss per trade ($20)

2. Data acquisition module

• Purpose: Fetch and process real-time SOL price data.

• Components:

  WebSocket connection to Solana blockchain or exchange API (e.g., Serum, Raydium, or centralized exchange like Binance)

  1-minute OHLCV (Open, High, Low, Close, Volume) data stream

  Data buffer for storing recent price history

  Error handling for connection drops or latency

3. Volatility analysis module

• Purpose: Assess SOL’s price volatility to inform trade decisions.

• Components:

  Placeholder: Calculate short-term volatility (e.g., standard deviation or ATR over one-minute candles)

  Placeholder: Define volatility thresholds (e.g., high/low volatility states)

  Output: Volatility score or signal to adjust trade frequency/size

4. Trade signal generator

• Purpose: Generate buy/sell signals based on price fluctuations.

• Components:

  Placeholder: Simple momentum strategy (e.g., price crossing a short-term moving average)

  Placeholder: Filter signals using volatility analysis

  Signal validation (e.g., avoid over-trading within one-minute window)

  Output: Buy/sell signal with timestamp

5. Risk management module

• Purpose: Enforce risk controls and position limits.

• Components:

  Position size calculator (fixed at $100 per trade)

  Max loss check ($20 per trade stop-loss)

  Total profit/loss tracker (halt at $50 profit or after 10 trades)

  Concurrent trade limiter (cap at 10 active positions)

  Emergency stop (pause bot on extreme volatility or connectivity loss)

6. Trade execution module

• Purpose: Execute trades on the Solana blockchain or exchange.

• Components:

  Placeholder: Build Solana transaction (e.g., swap SOL for USDC via a DEX like Raydium)

  Order type (market order for speed in one-minute timeframe)

  Slippage tolerance (e.g., 0.5% max slippage)

  Transaction signing and submission

  Confirmation listener (await transaction finality)

  Error handling (e.g., retry on failed execution)

7. Performance monitoring module

• Purpose: Track and log bot performance in real time.

• Components:

  Trade log (entry price, exit price, profit/loss, timestamp)

  Running total profit/loss calculator

  Performance metrics (e.g., win rate, average trade duration)

  Alert system (notify on profit target, max loss, or errors)

8. Main control loop

• Purpose: Orchestrate bot operations in a continuous cycle.

• Components:

  Initialize bot (load config, connect to data feed)

  Loop:

  Fetch one-minute price data

  Analyze volatility

  Generate trade signal

  Apply risk management checks

  Execute trade if conditions met

  Update performance metrics

  Exit conditions (profit target hit, max trades reached, or manual stop)

9. Shutdown and cleanup

• Purpose: Safely terminate the bot and finalize operations.

• Components:

  Close open WebSocket connections

  Finalize pending transactions

  Save trade log and performance summary

  Release resources (e.g., memory, wallet connections)

Notes

• This framework assumes integration with Solana’s ecosystem (e.g., using a DEX or liquidity pool). Adjust the execution module if targeting a centralized exchange.

• Volatility analysis and signal generation are left as placeholders for customization (e.g., technical indicators or machine learning models).

• Risk management is strict to align with the $50 profit goal and $20 max loss per trade, ensuring the bot operates within defined boundaries.

Caution! The above is a tailored outline shaped by the user’s prompt, targeting one-minute price fluctuations, risk management and trade execution. Its output varies with prompt detail, as specificity sharpens results. Moreover, placeholders like volatility analysis await user customization, reflecting Grok 3’s adaptive learning. It’s a conceptual guide, not code, and success hinges on implementation and market conditions. For deeper refinement, such as Solana-specific tweaks, users can provide more context. Grok 3 adjusts using their input and its latest insights.

Let’s learn the general steps required to set up Grok 3 for automated crypto trading.

How to set up Grok 3 for automated crypto trading

Setting up Grok 3 for AI-powered crypto trading automation isn’t as straightforward as installing a typical trading bot. Since Grok 3 wasn’t built for direct trading, it requires thoughtful setup, integration and customization. Below is a practical guide to setting up Grok 3 effectively for automated crypto trading with AI (artificial intelligence).

Step 1: Choosing a compatible trading platform

Since Grok 3 doesn’t connect directly to crypto exchanges, it requires integration with third-party platforms that support API automation. Platforms like:

• 3Commas: Ideal for executing trades via automated strategies.

• TradingView: Used for generating trade signals using Pine Script.

• CryptoHopper: Offers custom strategy-building tools with API integration.

Ensure that the chosen platform offers robust API support for managing trade execution, setting risk controls and tracking performance.

Step 2: Integrating Grok 3 with the trading platform

Grok 3 doesn’t connect directly to crypto exchanges; integration requires creative workarounds:

• API integration via automation tools: Platforms like Zapier or Make.com can connect Grok 3’s analysis to trading platforms.

• Custom Python scripts: For tech-savvy traders, Grok 3’s insights can be processed through Python scripts that execute trades based on Grok 3’s recommendations.

• No-code automation tools: Services like IFTTT can trigger basic trading actions based on Grok 3’s sentiment analysis.

Step 3: Defining trading strategies with Grok 3

Grok 3’s success hinges on well-defined strategies. Unlike traditional bots that rely solely on technical signals, Grok 3 crypto trading bot can combine multiple factors, including:

• Technical indicators: RSI, MACD, Bollinger Bands, etc.

• Sentiment analysis: Social media trends, influencer opinions and news headlines

• Onchain data: Whale activity, exchange inflows/outflows and large wallet movement.

Step 4: Backtesting strategies before live trading

Before deploying Grok 3’s strategy in live markets, backtesting is essential to evaluate its performance. Backtesting can reveal:

• Accuracy of trade signals: Identify how often Grok 3’s suggested trades align with profitable outcomes.

• False signal detection: Ensure Grok 3 isn’t generating excessive buy/sell recommendations in volatile or stagnant markets

• Refinement opportunities: Fine-tune conditions such as RSI thresholds, sentiment scores or trade exit conditions

Examples of tools for backtesting include TradingView and CryptoQuant.

Step 5: Implementing risk management controls

Even with solid insights, crypto markets are unpredictable. Adding risk controls minimizes potential losses:

• Stop-loss orders: Automatically exits trades if prices move beyond a set threshold.

• Position limits: Restricts trade size to reduce exposure in uncertain markets.

• Trailing stops: Locks in profits during upward trends while minimizing downside risk.

Example of risk control prompt:
“Write a code to handle buying and selling a token with the given parameters, including priority fees, slippage, and a take-profit mechanism.”

Please note that the output shown above is not complete and is provided for illustration purposes only.

Step 6: Ongoing monitoring and strategy refinement

Grok 3’s strength lies in its adaptability, but it requires ongoing monitoring to ensure optimal results. Regularly review:

• Performance data: Assess win rates, profit margins and signal accuracy.

• Market conditions: Adjust strategy if major shifts (e.g., regulatory changes or macroeconomic factors) impact sentiment or momentum.

Pro tip: Revisiting Grok 3’s prompts regularly can refine strategy outcomes and improve long-term performance.

Limitations of Grok 3

Despite its strengths, Grok 3 has limitations that traders must consider. 

• Data loss: Crypto trading thrives on accurate and real-time data. However, crypto trading automation with Grok 3 has been reported to lose chunks of data, miscount words and provide incorrect time references, which can be detrimental in a fast-moving market and result in inaccurate signal detection, delayed responses to market events and flawed strategy execution.

• No direct exchange integration: Unlike purpose-built trading bots, Grok 3 doesn’t connect directly to crypto exchanges. Traders must rely on third-party platforms to execute trades.

• Forgetfulness: One of the biggest frustrations highlighted by some users is Grok 3’s “retrograde amnesia,” when it forgets everything from previous sessions. For crypto traders, this is a nightmare. Imagine building a trading strategy and needing Grok 3 to remember past trends and conversations, only for it to start fresh each session.

• Bias: Grok 3 may deliver biased responses, potentially relying on incomplete or skewed sources. For traders who depend on unbiased sentiment analysis to gauge market mood, this shift could lead to misleading insights and poor decision-making.

• Slower execution speed: Since Grok 3 processes information based on detailed prompts, its trade signals may lag behind fast-moving price changes.

• Prompt dependence: Grok 3’s accuracy depends heavily on well-structured prompts. Vague or incomplete instructions often produce unreliable results.

While Grok-3 and other AI systems offer powerful tools for automating crypto trades, caution is essential. Their performance depends heavily on the quality of data and the strategies they’re programmed with, meaning unexpected market shifts or flawed inputs can lead to significant losses. 

Remember, AI lacks human intuition and may struggle with unprecedented events, so relying solely on it without oversight is risky. Always test strategies with small amounts first and get help from experts before making large investments.

Nearly 400,000 creditors of the bankrupt cryptocurrency exchange FTX risk missing out on $2.5 billion in repayments after failing to begin the mandatory Know Your Customer (KYC) verification process.

Roughly 392,000 FTX creditors have failed to complete or at least take the first steps of the mandatory Know Your Customer verification, according to an April 2 court filing in the US Bankruptcy Court for the District of Delaware.

FTX users originally had until March 3 to begin the verification process to collect their claims.

“If a holder of a claim listed on Schedule 1 attached thereto did not commence the KYC submission process with respect to such claim on or prior to March 3, 2025, at 4:00 pm (ET) (the “KYC Commencing Deadline”), 2 such claim shall be disallowed and expunged in its entirety,” the filing states.

The KYC deadline has been extended to June 1, 2025, giving users another chance to verify their identity and claim eligibility. Those who fail to meet the new deadline may have their claims permanently disqualified.

According to the court documents, claims under $50,000 could account for roughly $655 million in disallowed repayments, while claims over $50,000 could amount to $1.9 billion — bringing the total at-risk funds to more than $2.5 billion.

The next round of FTX creditor repayments is set for May 30, 2025, with over $11 billion expected to be repaid to creditors with claims of over $50,000.

Under FTX’s recovery plan, 98% of creditors are expected to receive at least 118% of their original claim value in cash.

Related: FTX liquidated $1.5B in 3AC assets 2 weeks before hedge fund’s collapse

How FTX users can complete KYC

Many FTX users have reported problems with the KYC process.

However, users who were unable to submit their KYC documentation can resubmit their application and restart the verification process, according to an April 5 X post from Sunil, FTX creditor and Customer Ad-Hoc Committee member.

Impacted users should email FTX support ([email protected]) to receive a ticket number, then log in to the support portal, create an account, and re-upload the necessary KYC documents.

Related: Crypto trader turns $2K PEPE into $43M, sells for $10M profit

FTX’s Bahamian subsidiary, FTX Digital Markets, processed the first round of repayments in February, distributing $1.2 billion to creditors.

The crypto industry is still recovering from the collapse of FTX and more than 130 subsidiaries launched a series of insolvencies that led to the industry’s longest-ever crypto winter, which saw Bitcoin’s (BTC) price bottom out at around $16,000.

While not a “market-moving catalyst” in itself, the beginning of the FTX repayments is a positive sign for the maturation of the crypto industry, which may see a “significant portion” reinvested into cryptocurrencies, Alvin Kan, chief operating officer at Bitget Wallet, told Cointelegraph.

Magazine: XRP win leaves Ripple a ‘bad actor’ with no crypto legal precedent set

Crypto-friendly billionaire investor Bill Ackman is considering the possibility that US President Donald Trump may pause the implementation of his controversial proposed tariffs on April 7.

“One would have to imagine that President Donald Trump’s phone has been ringing off the hook. The practical reality is that there is insufficient time for him to make deals before the tariffs are scheduled to take effect,” Ackman, founder of Pershing Square Capital Management, said in an April 5 X post.

Trump may postpone tariffs to make more deals, says Ackman

“I would, therefore, not be surprised to wake up Monday with an announcement from the President that he was postponing the implementation of the tariffs to give him time to make deals,” Ackman added.

On April 2, Trump signed an executive order establishing a 10% baseline tariff on all imports from all countries, which took effect on April 5. Harsher reciprocal tariffs on trading partners with which the US has the largest trade deficits are scheduled to kick in on April 9.

Ackman — who famously said “crypto is here to stay” after the FTX collapse in November 2022 — said Trump captured the attention of the world and US trading partners, backing the tariffs as necessary after what he called an “unfair tariff regime” that hurt US workers and economy “over many decades.” 

Following Trump’s announcement on April 2, the US stock market shed more value during the April 4 trading session than the entire crypto market is currently worth. The fact that crypto held up better than the US stock market caught the attention of both crypto industry supporters and skeptics.

Prominent crypto voices such as BitMEX co-founder Arthur Hayes and Gemini co-founder Cameron Winklevoss also recently showed their support for Trump’s tariffs.

Related: Trump tariffs squeeze already struggling Bitcoin miners — Braiins exec

Ackman said a pause would be a logical move by Trump — not just to allow time for closing potential deals but also to give companies of all sizes “time to prepare for changes.” He added:

“The risk of not doing so is that the massive increase in uncertainty drives the economy into a recession, potentially a severe one.”

Ackman said April 7 will be “one of the more interesting days” in US economic history.

Magazine: New ‘MemeStrategy’ Bitcoin firm by 9GAG, jailed CEO’s $3.5M bonus: Asia Express

The White House AI and crypto czar David Sacks says Meta’s release of its latest AI model, Llama 4, has pushed the United States into the lead in the global race for artificial intelligence dominance.

“For the US to win the AI race, we have to win in open source too, and Llama 4 puts us back in the lead,” Sacks said in an April 5 X post, as speculation continues to mount over the US and China competing for the top spot in the global AI race.

Sacks has been outspoken about the AI race since taking on his role following US President Donald Trump’s inauguration on Jan. 20. Just over a week into the job, Sacks said he is “confident in the US, but we can’t be complacent.”

Llama 4 “best in their class for multimodality,” says Meta

Sack’s latest comment came after Meta’s AI division said in an X post on the same day that it is introducing the fourth generation of its Llama models, Llama 4 Scout and Llama 4 Maverick.

“Our most advanced models yet and the best in their class for multimodality,” Meta said.

Meta said its Llama 4 Scout model has 17 billion active parameters and uses 16 experts. 

The company claims it outperforms rival large language models — Gemma 3, Gemini 2.0 Flash-lite, and Mistral 3.1 — “across a broad range of widely accepted benchmarks.”

Meanwhile, Llama 4 Maverick also has 17 billion active parameters but is configured with 128 experts. Meta claimed the Maverick model can outperform GPT-4o and Gemini 2.0 Flash “across a broad range of widely accepted benchmarks.” 

It also said Maverick can perform similarly to DeepSeek v3 on “reasoning and coding tasks” despite using only half the active parameters.

Related: NFT marketplace X2Y2 shuts down after 3 years, pivots to AI

Less than a year ago, in July 2024, Meta CEO Mark Zuckerberg said that in 2025, he expects Llama models to become “the most advanced in the industry.” It has been just over two years since Meta first released the limited version of Llama 1 in February 2023.

At the time, Meta said it was “blown away” by the demand, receiving over 100,000 requests for access. 

Magazine: XRP win leaves Ripple a ‘bad actor’ with no crypto legal precedent set

Traders on the Kalshi prediction market place the odds of a US recession in 2025 at 61%, following the sweeping tariff order signed by President Donald Trump on April 2.

Kalshi uses the standard criteria of a recession, two business quarters of negative gross domestic product (GDP) growth, as reported by the United States Department of Commerce.

Odds of a US recession on the prediction platform have nearly doubled since March 20 and mirror the current 2025 US recession odds on Polymarket, which traders on the platform currently place at 60%.

The macroeconomic outlook for 2025 deteriorated rapidly following US President Donald Trump’s sweeping tariff order and the ensuing sell-off in capital markets, sparking fears of a prolonged bear market.

Related: Bitcoin bulls defend $80K support as ‘World War 3 of trade wars’ crushes US stocks

Trump’s executive order throws markets in disarray

The US President’s executive order established a 10% baseline tariff rate for all countries and different “reciprocal” tariff rates on trading partners with existing tariffs on US import goods.

Trump’s announcement triggered an immediate stock market sell-off, wiping away over $5 trillion in shareholder value in a matter of days.

Fears of a recession continue to grow as market analysts warn of a potentially protracted trade war that negatively impacts global markets and suppresses risk asset prices, including cryptocurrencies.

Meanwhile, President Trump has expressed confidence that the tariffs will strengthen the US economy long-term and correct any trade imbalances.

“The markets are going to boom,” the President said on April 3, describing the current market sell-off as an expected part of the process.

Asset manager Anthony Pompliano recently speculated that President Trump deliberately crashed markets to bring down interest rates.

Pompliano cited the reduction in 10-year US Treasury bonds as evidence that the President’s strategy of forcing a recession to impact rates is working.

Interest rates on 10-year US Treasury bonds declined from approximately 4.66% in January 2025 to just 4.00% on April 5. President Trump is also pressuring Federal Reserve chairman Jerome Powell to lower short-term interest rates.

“This would be a perfect time for Fed chairman Jerome Powell to cut interest rates,” Trump wrote in an April 4 Truth Social post.

Magazine: Financial nihilism in crypto is over — It’s time to dream big again

Solana’s native token SOL (SOL) dropped by 9% between March 28 and April 4, but several key metrics grew during the same period. Despite SOL’s price downturn, the Solana network continues to outpace competitors, maintaining its second-place position in deposits and trading volume. Traders now wonder how long it will take for SOL’s price to reflect this onchain strength.

Solana outperforms rivals in TVL deposits and DEX volumes

Investor’s declining interest in SOL could be linked to the April 4 staking unlock of 1.79 million SOL, worth over $200 million. The selling pressure is clear, as these tokens were staked in April 2021, when SOL traded near $23. Another factor is the decline in interest for memecoins, which had been a major driver of new user adoption on Solana. With fewer speculative inflows, growth in activity may not translate to immediate price gains.

Several meme-themed cryptocurrencies, including WIF, PENGU, POPCAT, AI16Z, BOME, and ACT, saw declines of 20% or more over the past seven days. Yet, despite worsening market conditions, the Solana network outperformed some competitors. Its Total Value Locked (TVL) rose to the highest level since June 2022, while decentralized exchange (DEX) volumes showed notable resilience.

Deposits in Solana network’s DApps rose to 53.8 million SOL on April 2, marking a 14% increase from the previous month. In US dollar terms, the $6.5 billion total stands $780 million ahead of its closest competitor, BNB Chain. Solana’s top DApps by TVL include Jito (liquid staking), Jupiter (leading DEX), and Kamino (lending and liquidity platform).

Solana gains support for scalability, and Web3 focus despite MEV concerns

While not yet a direct threat to Ethereum’s $50 billion TVL, Solana’s onchain data shows greater resilience compared to BNB Chain, Tron, and Ethereum layer-2 networks like Base and Arbitrum. In decentralized exchange (DEX) volumes, Solana holds a 24% market share, while BNB Chain accounts for 12% and Base captures 10%, according to data from DefiLlama.

While Ethereum has regained the lead in DEX volumes, Solana has shown strong resilience following the memecoin bubble burst. For context, Raydium’s weekly volumes dropped 95% from the $42.9 billion all-time high reached in mid-January. Still, Solana has demonstrated that traders appreciate its focus on base layer scalability and integrated Web3 user experience despite ongoing criticism related to maximum extractable value (MEV).

In short, MEV occurs when validators reorder transactions for profit. This practice is not unique to Solana, but some market participants—such as user Cbb0fe, a self-proclaimed decentralized finance (DeFi) liquidity provider—have raised concerns about insider gatekeeping. While not stated directly, the criticism likely refers to incentives provided by Solana Labs to offset the high investment and maintenance costs required by certain validators.

Supporters of changing Solana’s token emissions argue that rewards earned through MEV already provide sufficient incentives for validators to secure the network, eliminating the need for further inflationary pressure on SOL. Meanwhile, Loring Harkness, a core contributor to Shutter Network, advocates for encrypting transactions before they enter the mempool as a way to prevent validators from manipulating their order.

Solana’s growth in TVL and resilience in DEX market share may not be enough for SOL to retest the $200 level seen in mid-February. However, it has firmly secured its second-place position behind Ethereum as a leading platform for decentralized applications, supported by consistent activity, infrastructure development, and growing interest from both developers and users.

This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.