MEV: Unresolved Multi-Objective Optimization

No matter which Block chain infrastructure you use, it is recommended to connect to a private trading pool/Private RPC Node as much as possible when conducting AMM-related transactions to reduce the risk of transactions being exposed to public pools.

Written by: Siyuan H, Dana H

Source: YZi Labs

TL;DR

MEV is an old topic faced by every Block chain, involving multiple roles such as users, DeFi protocols, public chain foundations, validators, and searchers in a complex game, and therefore, this old topic always has new trends, bringing new interesting research topics.

How should the MEV ecosystem of a public chain be designed? This is a typical multi-objective optimization problem with no absolute correct answer. Therefore, by observing the current state and future development of MEV ecosystems on various Layer 1 public chains, we can reveal their value propositions and assess their priorities in multi-objective optimization.

MEV takes various forms, and there is currently no standard definition of malicious MEV, but 'sandwich attacks' (i.e. 'sandwiching') do indeed harm the interests of ordinary users. If a user's AMM transaction is sandwiched, two conditions must be met: 1) the transaction pair is visible to the attacker; 2) the user has set a relatively high slippage tolerance, creating opportunities for arbitrage. Therefore, to avoid being sandwiched, users should: 1) maximize transaction privacy, or 2) reduce slippage tolerance to minimize the attacker's arbitrage opportunities.

This article analyzes the current situation and subsequent plans of MEV on various public chains, using Ethereum, BSC, and Solana as examples, and explores the value propositions reflected therein.

  • Ethereum prioritizes decentralization
  • BSC prioritizes protecting users' trading experience
  • Solana prioritizes transaction efficiency and market competition

Acknowledgments: Thank you to the detailed Solana MEV report from the Helius(@heliuslabs) team, the sincere sharing from the BNB Chain(@BNBCHAIN) core dev team, the efforts in MEV transparency from the #Flashbots team, Jito(@jito_labs) team, and EigenPhi(@EigenPhi) team, as well as the data contributors on Dune(@Dune). The data cited in the article is from your detailed work. Finally, thanks also to TrustWallet(@TrustWallet), PancakeSwap(@PancakeSwap), GMGN(@gmgnai), and other teams for their efforts in user education and MEV protection.

MEV - An old topic that has always been evolving

On March 10, 2025, Jito's data dashboard displayed a decrease in the Solana on-chain Bundle transaction volume and Tips. Some users reported an increase in the number of sandwich attacks on SOL, prompting a renewed discussion of the MEV issue.

In the past two months, with the surge in trading volume on BSC (especially for meme coins traded by ordinary users), malicious MEV on BSC (especially the sandwich attacks commonly known as 'sandwiches') has been criticized by community users. In response, BSC is trying to reduce malicious MEV and optimize the experience for ordinary users by significantly shortening Block time, changing the consensus mechanism for on-chain transactions, etc.

On Ethereum, the MEV topic has always been a focus of community attention and discussion. In March 2025, anonymous researcher Malik672 proposed a 'decentralized random Block proposal' system aimed at eliminating MEV through the randomization of the Block selection process. The system uses a shared random algorithm and Byzantine Fault Tolerance (BFT) mechanism to ensure that all Ethereum clients (such as Geth and Nethermind) can participate in Block construction, rather than being limited to a few large builders.

MEV is not a unique phenomenon of any specific public chain such as Solana, Ethereum, or BSC, but a complex problem that all Blockchains ecosystems will face. Essentially, MEV is a multi-objective optimization problem, and there is no absolute correct path. In a distributed and decentralized Blockchain network, various parties engage in a game of interests, each with their own objective functions to maximize. Ultimately, the solution chosen by a particular chain reflects the spiritual state and value orientation of that chain.

Fig 1a. Jito Bundles and Tips data

Fig 1b. Jito data overview(2025.3.10)

According to official data from Jito, the number of transaction bundles processed by Jito per day will remain between 13M-20M until March 9, 2025, with a daily income of about 10,000-15,000 SOL in tips. However, starting from March 9, the daily tips income has also decreased to around 8,000 SOL. Nevertheless, Jito's revenue is still very substantial.

Taking this as an opportunity, we deeply contemplate the essence. Why do ordinary users get sandwiched? Why do they choose Jito? What kind of existence is MEV for public chains? What is the current situation of MEV on various public chains? How to handle MEV correctly? What will be the future of MEV on major L1 public chains? Let's start the next reading with these questions in mind.

Why does MEV exist widely? Where does the "sandwich" come from?

The core reason why MEV is a universal issue in all Block blockchain networks is that most Block blockchain networks follow the same pattern in their architecture. We use a brief model to describe this process.

After the user sends a transaction instruction through the wallet, the wallet first sends the transaction to the RPC Node, and then the RPC Node forwards the transaction to the validation Node (Validator) in the Block chain network, or the RPC Node itself acts as the Validator. Before the transaction is officially packaged into the Block, the Validator temporarily stores the received transactions in a temporary memory area inside the Node. This memory area is called different names on different chains, such as transaction pool (Mempool/TxPool/Tx Queue, etc.). Whenever the Validator has the privilege to package the Block, it selects a certain number of transactions from the transaction cache area, combines them into a Block according to specific rules, and publishes it to the Block chain network.

In the initial design of the Blockchain, Validators typically determine the order of transactions based on the level of transaction fees paid by users (Tx Fee or Gas Fee), where higher fees mean transactions will be processed first. However, with the rise of decentralized finance (DeFi) applications, especially automated market makers (AMM), transaction ordering has brought additional arbitrage opportunities beyond fees, resulting in the so-called Maximal Extractable Value (MEV).

MEV refers to the behavior of miners or validating Nodes (Validators) in the Blockchain, who obtain additional economic benefits from applications such as DeFi by reordering transactions, inserting additional transactions, or selectively packaging specific transactions. Some of these behaviors are malicious and harmful to ordinary users. The most typical example is the 'Sandwich Attack.' This type of attack usually occurs on decentralized exchanges (DEX) of automated market makers (AMM). When users trade on AMM, attackers first submit a transaction to front-run the user's trade, driving up (or down) the price of the asset, and then immediately submit a reverse transaction after the user's trade is completed to profit from artificially manipulating the price difference. The profitability of the Sandwich Attack depends on the 'Slippage' parameter set in the user's transaction, which is the proportion that allows the final transaction price to deviate from the initial expected price. The higher the slippage set, the greater the profit space for attackers from the Sandwich Attack.

It is important to emphasize that there are three necessary prerequisites for a successful sandwich attack:

  • User transactions are exposed in the transaction pool visible to attackers, allowing attackers to discover target transactions in advance
  • The front and back sandwich transactions submitted by the attacker were successfully included in the same Block ( in most cases, or in consecutive Blocks.
  • After the final Block is confirmed and added to the Blockchain, the transaction price of users is significantly affected by the attacker's transactions, known as 'sandwiched'.

Therefore, for ordinary users, preventing MEV means solving two core issues:

  • How to avoid exposing your transactions to potential attackers (i.e. solving the issue of transaction 'visibility')?
  • How to ensure that your transactions can be packaged into blocks by Validators faster and more reliably, to reduce delays and uncertainties?

From the perspective of Validators, they hope to maximize their own economic interests, which is reflected in how to better select high-value transactions, while capturing additional income generated by more MEV.

In this context, two specialized roles, Searcher and Builder, have gradually emerged for optimizing MEV in different Blockchain ecosystems.

  • Searcher is a role specifically responsible for scanning the transaction pool to discover potential MEV arbitrage opportunities. They proactively identify high-value transactions in the mempool, construct transaction bundles containing arbitrage, sandwich attacks, or liquidation transactions, and then submit these transaction bundles to the Builder, usually accompanied by additional 'tips' to ensure that their transactions are prioritized for packaging.
  • Builder) primarily exists in the on-chain ( under the PBS architecture, and is responsible for filtering, sorting, and optimizing the transaction package submitted by Searcher, in order to form a Block structure with higher value and more easily accepted by Validator, thus helping Validator capture MEV revenue quickly and efficiently.

Validators typically do not refuse to cooperate with Builder and Searcher, as this pattern can provide them with stable economic returns and form an effective chain of interest distribution. In fact, this multi-party game pattern has gradually become an important part of the MEV ecosystem, continuously driving the optimization and competition of MEV infrastructure.

Each Blockchain ecosystem will produce different MEV response solutions according to its own characteristics. For example, Jito, widely used on Solana, is a specialized infrastructure born to find the best balance between Validators, Searchers, and users, specifically optimized for MEV issues.

Solana's MEV ecosystem: transaction efficiency dominates, Jito mechanism shapes the market

Jito as the mainstream MEV mechanism: speeding up transactions, users voluntarily bear the cost of MEV

Jito is the primary MEV transaction sorting tool on Solana, with the core mechanism of building a special private transaction pool (Private Mempool). Users' transactions are not immediately exposed to the network after submission, but are temporarily stored in a private environment (Private Mempool), effectively avoiding the possibility of attackers discovering user transactions in advance and launching sandwich attacks. At the same time, Jito introduces an economic incentive mechanism, allowing users to pay additional 'tips' to incentivize Validators to prioritize processing their transactions, thereby improving transaction efficiency while protecting user interests.

Jito's MEV operates by allowing Searchers to submit transaction bundles with tips through Jito Bundles, which are prioritized and executed by validators. Over the past year, Jito has processed over 3 billion transaction bundles, generating a total of over 3.75 million SOL in Tips fees. Just in the past year, the number and scale of transaction bundles processed by Jito far exceed similar MEV tools on Ethereum.

The performance of the Solana network is relatively high, with short Block times and a large number of Memecoin transactions. MEV transactions on the chain usually appear in the form of 'small amounts, high frequency'. This characteristic leads to small profits from arbitrage and sandwich attacks for a single transaction, but the trading volume is extremely large. Taking sandwich attacks as an example, on the Solana chain, the average extracted value per attack is about 0.0425 SOL (about $8.7), far lower than the amount per transaction on Ethereum, but the overall number of transactions is considerable.

In summary, MEV on Solana has the following characteristics

  • High-frequency trading with small transaction amounts: MEV transactions in the Jito ecosystem are mainly composed of a large number of small transactions. For example, MEV bots on Solana executed 90,445,905 arbitrage transactions in 2024, but the average profit per transaction was only $1.58.
  • Users are willing to pay fees to increase transaction priority: Jito users can preempt transaction sequencing rights by paying additional tips. For example, in November 2024, Jito prompt fees surged to 60,801 SOL/day, indicating that users are willing to bear higher MEV-related costs when the market is active.
  • Competition for front-running affects user slippage costs: On Solana, some high-frequency traders use tools like Telegram bots to buy tokens, often setting high slippage tolerance to ensure successful trades. This results in them almost always trading within the maximum slippage range, effectively voluntarily surrendering some value to MEV bots. Data shows that the average value extracted per single sandwich attack on Solana is approximately 0.0425 SOL ($8.7).

Other MEV mechanisms: Private Mempool solutions outside of Jito

Although Jito is the primary trading acceleration tool, it does not cover all MEV activities on Solana, and the private Mempool solution has become another major competitive model.

  • DeezNode Private Mempool: Some validators (such as DeezNode) run a private Mempool, allowing searchers to bypass Jito and pay validators high fees directly to prioritize transaction packaging. In the past 30 days, the number of sandwich attacks in this mechanism has reached 1,550,000 transactions, with a total profit of 65,880 SOL (about 13.43 million USD), and an average profit of 0.0425 SOL per transaction.
  • Paladin-Solana Anti-Sandwich Solution: Some Solana Nodes (6% of the total network staking) adopt the Paladin solution, proactively discarding sandwich attack transaction packages, and providing a compensation mechanism through staking PAL tokens in an attempt to improve the fairness of transaction ordering.

From the perspective of user behavior, users are more concerned about whether the transaction can be executed quickly, rather than the cost details of a single transaction. Especially due to the frequent appearance of hot projects such as Meme coins in the Solana ecosystem, many users tend to participate in 'new listings' quickly through automated trading bots, and the specific details of the transaction are usually ignored or completely isolated by users. Users generally do not pay attention to whether the bot has integrated Jito or the impact of MEV sandwich attacks during the transaction process.

Therefore, the MEV phenomenon on Solana is also widespread, and due to the widespread use of high-frequency trading and automated Bots, MEV activities are more active. Currently, the MEV solutions in the Solana ecosystem do not completely eliminate MEV, but rather form a dynamic equilibrium among different market participants (users, Bots, validators, searchers) under the interests game and market competition. The existence of mechanisms like Jito is not only the result of market demand but also a reflection of different roles seeking the optimal profit strategy in the MEV ecosystem.

Analysis of the current situation of MEV on Ethereum: decentralized solutions, compression of arbitrage space, and dominance of whales in the DeFi ecosystem

As the birthplace of DeFi, Ethereum has long been the focal point of MEV (Maximum Extractable Value) issues. In response to on-chain challenges such as sandwich attacks, researchers at the Ethereum Foundation have not only proposed the Proposer-Builder Separation )PBS( model, but also dedicated themselves to protecting the Ethereum ecosystem from the negative impact of MEV through continuous research and development. The Foundation has collaborated with the ecosystem infrastructure project Flashbots to balance the demands of all participants through the PBS model. Flashbots has introduced a transparent and permissionless auction mechanism to standardize the MEV extraction process by increasing transparency and ensuring fairer distribution of profits among validators, users, and other stakeholders.

According to Flashbots data, the average daily MEV revenue on the Ethereum mainnet exceeded $500,000 in 2023. By 2024, with the rapid development of the Ethereum Layer 2 ecosystem, some MEV trading opportunities have been diverted. As of now, the MEV revenue level on Ethereum Layer 1 has stabilized at around $300,000 per day.

However, after entering 2025, the MEV ecosystem on Ethereum remains active, but the overall profitability shows a significant downward trend. Data from March 4, 2025, shows that although sandwich attacks accounted for as much as $289.76 million in trading volume, representing 51.56% of all MEV trading volume ($561.92 million), the actual profit generated was only $6,320, accounting for 4.11% of the total MEV profit. This data intuitively reflects a significant decrease in the single transaction profitability of sandwich attack strategies. During the same period, the total cost of Ethereum MEV increased by 28.36% to $358,850, while total revenue only increased by 6.90% to $512,660, resulting in net profit being significantly compressed to $153,810. This indicates that although MEV transactions still occur frequently, due to intense competition and cost increases, as well as the improvement of infrastructure to prevent sandwich attacks, the overall profit space is continuously shrinking.

The current status of MEV transactions on Ethereum: dominated by institutions and whales

Due to the high Gas fees on the Ethereum L1 network, retail users tend to transfer to L2 solutions like Base, Arbitrum, or other lower-cost public chains for small transactions. As a result, the main participants in MEV transactions on the Ethereum mainnet are gradually concentrating among institutions, whales, and specialized market makers. Large MEV transactions prove that Ethereum L1 remains the most important liquidity hub in the DeFi space, but this high liquidity also means that large transactions are more likely to incur higher slippage, creating continuous arbitrage opportunities for MEV bots.

Since 2025, the single transaction profit of sandwich attacks in the Ethereum ecosystem has significantly decreased, the reasons behind which include:

  • Market competition intensifies: The number of MEV bots has significantly increased, leading to the rapid compression of profits from simple arbitrage strategies such as sandwich attacks.
  • Institutional traders' strategy optimization: Many institutions are increasingly adopting trading methods such as Time-Weighted Average Price (TWAP) and Dollar-Cost Averaging (DCA) to reduce the size of individual trades, thereby reducing the possibility of being exploited for arbitrage by MEV robots.
  • The widespread use of MEV defense tools: Private transactions, flash swaps (Batch Auctions), Order Flow Auctions (OFA), and other trading mechanisms are gradually becoming popular, significantly reducing the space for traders to be sandwich attacked or frontrun for arbitrage.

The Future of Ethereum MEV: Evolution of Arbitrage Models, Gradually Forming a More Professional Ecosystem

With the development of the Ethereum L2 ecosystem, more and more DeFi transactions and MEV opportunities are being diverted to L2, further weakening the MEV opportunities on L1. However, as L1 remains the primary venue for high liquidity and institutional-grade DeFi activities, MEV will not disappear but evolve towards more complex strategies. For example:

  • Arbitrage is still the primary MEV opportunity, especially in cross-chain arbitrage between L1 and L2.
  • Liquidation has become the new focus, with the growth of the DeFi lending market, large-scale liquidation transactions are still the target pursued by MEV bots.
  • The new MEV mechanism, such as Order Flow Auctions (OFA), may change the way MEV operators profit, making them more inclined to collaborate directly with liquidity providers and protocols, rather than just profit from the slippage of counterparties.

Overall, the MEV ecosystem on Ethereum is undergoing structural changes. Since the MEV issue was raised, Ethereum has been continuously trying various solutions, including proposing architectural solutions such as PBS (Proposer-Builder Separation). While the profit space of simple sandwich attacks and front-running arbitrage has been significantly compressed, more complex and specialized MEV strategies are still emerging and evolving. This means that the MEV issue will persist on the Ethereum mainnet in the long term. In addition, the game of interests among searchers, Block builders, validators, users, and various MEV-related infrastructure projects (such as Flashbots) will continue for a long time. The competition revolving around transaction ordering, value capture, and fairness will drive the continuous evolution of the MEV ecosystem.

MEV ecosystem of BSC: The rapidly growing on-chain activities bring new requirements for the trading experience, with a priority to protect users' trading experience

Despite the frequent community attention to the malicious MEV issue in the BSC ecosystem, what is the actual situation?

According to data from Dune, starting in the second half of 2024, the proportion of sandwich attacks in all DEX trades on the BSC chain gradually increased, surpassing Ethereum for the first time in December 2024. Overall, the proportion of DEX trades on both BSC and Ethereum that were sandwich attacked did not exceed 8%. After reaching a peak in February 2025, the proportion of sandwich attacks in DEX trades on BSC fell to around 4%.

![])https://img.gateio.im/social/moments-6dbeb1269e260aa42a2d35c635575ea3(

Fig 2. ETH Sandwiched DEX Transaction vs BSC ETH SandWiched DEX Transaction

So why do many BSC users still frequently feel their trades are under attack? The main reason behind this is that recently, popular tokens have frequently appeared on BSC, leading to a significant increase in user on-chain transaction activities in the short term, thus raising awareness of MEV attacks.

To better understand this phenomenon, let's first review why users' transactions are susceptible to sandwich attacks:

  • Visibility of the transaction pool: After the user's transaction appears in the public transaction pool, attackers discover and construct sandwich transactions.
  • High slippage setting for transactions: Users set a higher slippage tolerance when conducting AMM transactions to ensure execution and actively provide arbitrage space.

Especially in periods of frequent trading of popular tokens, users' primary need is to complete buy transactions as quickly as possible to ensure they do not miss out on market trends. Therefore, they often actively set a higher slippage tolerance, indirectly providing more space for sandwich attacks. Although many wallets and Node provide solutions for MEV protection (such as private transaction pools or private RPC Nodes), not all users will choose these private transaction paths. In addition to users not paying attention to enabling MEV protection settings, on the one hand, private transactions do not speed up the packaging of user transactions; on the other hand, when transaction volume surges, transactions in public transaction pools are more easily discovered by Validators or Builders. If users appropriately increase transaction fees, transactions can be packaged more quickly. For example, ordinary stablecoin transfers or BNB transfers usually do not require additional MEV protection, and such transactions using public transaction pools may even be more efficient.

From a technical architecture perspective, the MEV ecosystem on BSC is similar to the PBS model on the Ethereum mainnet, where transaction ordering is created by the Builder and ultimately submitted to the Validator. Some Builders will provide Private Mempool services, but transactions in the public mempool may still be discovered and used to construct attack transaction packages by MEV searchers. Unlike the privacy transaction scheme on Solana, the privacy transaction pool on BSC does not significantly improve the priority or speed of user transactions being confirmed, but only provides a transaction privacy protection function.

Therefore, at the level of the public chain, truly solving the malicious MEV problem requires optimizing in two directions.

  • Improve the privacy of user transactions, avoid transactions being exposed in the public pool, thereby reducing the possibility of sandwich attacks;
  • Improve the processing performance of the Block chain itself, so that users' transactions can be packaged more quickly, such as shortening the block interval, increasing transaction throughput, and reducing the exposure window for attacks on transactions.

How is BSC addressing the MEV problem?

In the long run, BSC is trying to further reduce the negative impact of MEV on users through technical upgrades to the chain itself and performance optimization measures. In the latest roadmap, BSC has planned to shorten the Block production interval to within 750 milliseconds, officially entering the Sub-second era. This will bring the following two direct benefits:

  • Improve user experience: User transaction confirmation is faster, reducing the time transactions are exposed in the transaction pool and lowering the risk of MEV attacks.
  • Improved transaction security: Faster transaction confirmations reduce the probability of trade failures caused by slippage fluctuations, and indirectly compress the space for MEV bot arbitrage.

Therefore, although MEV activities on BSC continue to exist, their scale is not significantly more severe than on other chains. The development direction of the BSC chain is also very clear: by shortening the block interval to 750ms, gradually entering the sub-second era, starting from the performance of the chain itself and user experience, further alleviating the negative impact of MEV problems on users.

In addition to shortening the block time, BSC is also actively exploring the construction of a more comprehensive private transaction pool, such as achieving a user-centric Searcher, Validator game equilibrium through technologies like TEE.

Summary

Overall, the MEV issue is not unique to a specific Block chain, but a multi-target optimization challenge that all chains need to face. Currently, different ecosystems have adopted various strategies to seek a balance of interests among all parties:

  • Solana reduces the number of transactions visible to attackers through Jito and other private transaction pool mechanisms, and introduces a fee mechanism to improve transaction efficiency.
  • Ethereum adopts the PBS (Proposer-Builder Separation) system, making MEV competition more market-oriented and transparent.
  • BSC is improving the processing power of the chain and reducing the block interval to enhance user trading experience, reduce the risk of transactions being exposed to public transaction pools, and lower the risk of sandwich attacks.

For ordinary users, no matter which Blockchain infrastructure is used, it is recommended to try to access the private transaction pool / Private RPC Node as much as possible when conducting AMM-related transactions, in order to reduce the risk of exposing transactions to public pools and thus reduce the probability of suffering MEV attacks.

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Jito,

MEV-Boost Dashboard,

Solana MEV Report: Trends, Insights, and Challenges, Helius,

Proposer-builder separation,

Deeznode,

Flashbots,

EigenPhi,

Unlocking the Potential of MEV on BNB,

BEP-524,

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The content is for reference only, not a solicitation or offer. No investment, tax, or legal advice provided. See Disclaimer for more risks disclosure.
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