MegaETHMegaETH is a real-time blockchain that overcomes the performance limitations of the Ethereum Virtual Machine (EVM), aiming to achieve over 100,000 transactions per second, Gigagas/sec throughput, and millisecond-level end-to-end latency. Through data availability via EigenDA, specialized node architecture, and a two chain-views structure of EVM blocks and mini-blocks, it enables complex on-chain computations that were previously impossible on existing blockchains. Plus, MegaETH's real-time API optimized for low-latency access, enables developers to truly leverage its hyper-performance.
MegaETH adopted a meritocratic ecosystem strategy through MegaMafia, a rigorous accelerator program that selected 15 initial projects and required them to build natively on MegaETH. It also utilized community funding and NFT collections to build a community of genuine contributors, taking a differentiated approach to prevent project farming by fake communities.
The current MegaETH ecosystem consists primarily of MegaMafia projects, ranging from low-latency trading venue like Euphoria, GTE, Valhalla, and WCM, new CLOB-lending protocol like Avon, new trend trading protocol like Noise, and new interactive game experiences like Pump Party and Sweep. MegaMafia 2.0 projects are expected to be selected and announced soon, offering innovative user experiences based on MegaETH's high performance.
Source: MegaETH
EVM has often been criticized for being slow due to the low performance of Ethereum and early rollups. Ethereum has developed execution clients that could operate on minimal hardware to ensure decentralization, resulting in limitations on data processing capacity and the complexity of smart contracts.
Rollup chains were created to address these issues by compressing data and periodically submitting it to Ethereum. Despite this, directly submitting data to Ethereum still faced significant throughput constraints due to high costs and delays in state finalization. Consequently, chains aiming for high throughput chose Layer 1 structures, implementing their own virtual machines (VMs) for parallelized execution or consensus layers with fast finality, rather than implementing EVM L2s.
MegaETH emerged with a contrasting approach to building separate VMs for fast transaction processing. It argued that the EVM as an execution engine could deliver exceedingly high performance. MegaETH extensively identified and corrected bottlenecks in the existing EVM execution process. It drastically modified standardized Ethereum L2 structure to minimize dependency on consensus, maximizing EVM's execution speed. Through major reforms of EVM and L2 structures, MegaETH aims to build a high-performance EVM L2 chain capable of over 100,000 TPS (Transactions Per Second) with sub-millisecond latency. This advancement aspires to make applications, previously deemed impossible on existing blockchains, a reality.
MegaETH focuses significantly on both performance enhancements and user experience, evident in two key areas. First, it addresses elements that caused inconvenience in existing high-performance chains. Second, it aims to introduce applications that users have not encountered in other ecosystems.
To fully understand MegaETH's ecosystem, I believe readers should first grasp how MegaETH pursued extreme performance. Therefore, this article will first explain MegaETH's technical structure, followed by an introduction to the unique ecosystem MegaETH has built based on its high-performance chain.
2.1.1 EVM Bottleneck Identification and Improvement
Even before MegaETH, there had been continuous efforts to improve EVM execution speed, most of which adopted approaches to parallelize EVM. However, the MegaETH team verified through actual performance measurements that existing Rust-based EVM client (reth) could already process approximately 14,000 TPS, and pointed out through backtesting that approaches that simply parallelize EVM could achieve at most about double the performance improvement.
Beyond parallelization, MegaETH conducted experiments to identify which EVM opcodes caused computational delays. They discovered that opcodes responsible for reading and writing state values consumed nearly 50% of the computational time. To address this, MegaETH introduced two main approaches.
The first is changing the database structure. Instead of the Merkle Patricia Trie that EVM traditionally used to manage state values, MegaETH adopted a memory-efficient Verkle tree variant, maximizing the efficiency of state value updates. It also reduced unnecessary read/write operations by consolidating updates to state values that access the same memory area for a certain period.
The second is high-specification sequencer design. MegaETH designed sequencers to be equipped with ~100 GB of large-capacity RAM, allowing the entire blockchain state to be stored in memory. This eliminates CPU-memory delays that occur during SSD interaction for state value access, improving state value access speed by ~1,000x. Additionally, MegaETH recognized that the synchronization process of state values between sequencers and full nodes significantly affects block latency in high-performance blockchains. To address this, they created a block propagation protocol which allows for efficient utilization of network bandwidth, allowing for blocks created by the sequencer to be distributed throughout the network quickly and with reduced hardware requirements for full nodes.
2.1.2 Breaking Through Throughput Limitations via EigenDA Integration
Source: MegaETH
To achieve MegaETH's target performance of 100,000 transactions per second, bottlenecks in Data Availability (DA) must be addressed. Data availability layer makes transactions between state changes, allowing network participants to verify the network's state changes. Because MegaETH is a high-performance L2, it must submit large data volumes to Ethereum, which would exceed the capacity of Ethereum if done in entirety.
In 2024, Ethereum reduced rollup data submission costs to one-tenth through the Dencun hard fork. This change transitioned the data storage method for rollups from calldata to blobs. However, blob space remains limited, offering only about 64KB/s of DA throughput (which is a shared resource among all rollups), equating to roughly 400 TPS. Currently, Base alone consumes 25-30% of Ethereum's blob space, generating about 120 TPS of throughput. To meet its performance goals, MegaETH requires 20MB/s of throughput, ~312x of Ethereum's current capacity.
To address this limitation, MegaETH integrated with EigenDA, a data availability solution that enhances throughput using erasure-coded data sharding. This technique allows the system's capacity to increase linearly with the number of operators in the network. Currently, EigenDA offers 15MB/s of data availability throughput and has reached 50MB/s in its V2 testnet.
MegaETH has designed sequencers to periodically submit transaction data to EigenDA. This data is distributed and stored across EigenDA operators. These operators issue data availability certificates, which are verifiable through collective signatures in Ethereum's EigenDA validator contracts. Once verified, these certificates are sent by MegaETH sequencers to MegaETH inbox contracts on Ethereum.
At the same time, MegaETH submits state roots, which are cryptographic representations of MegaETH’s entire state, to Ethereum's bridge contracts. These state roots are used to verify blob data within EigenDA when fraud proof challenges arise.
2.2.1 Specialization of Node Operations
As explained earlier, MegaETH aims to separate execution from consensus entirely to eliminate phenomena where execution results are delayed by consensus, and chose L2 design to implement this. (Note: While there are various opinions on the definition of L2 chains, I consider all chains that submit states to Ethereum in some way (rollups / validium / optimium) to be L2.)
Currently, most L2s have sequencers perform most operations. The sequencer is responsible for bundling transactions into blocks, submitting constructed blocks to the network through broadcasting, and generating proofs to submit to Ethereum to verify that transactions were executed correctly. This series of processes is often implemented serially, causing the slowest operation to act as a bottleneck for sequencer processing speed.
MegaETH chose a structure that delegates work concentrated on sequencers to separate nodes with optimized hardware, allowing sequencers to focus on block generation. MegaETH consists of four types of nodes and light clients:
Sequencer Node: Like sequencers of other Layer 2 chains, it receives transactions from users and generates blocks. The sequencer node consists of high-performance servers requiring CPUs with over 100 cores, 1-4TB of RAM, and network connections of 10Gbps or higher. The sequencer stores the entire EVM state and state trie in memory using overwhelming RAM capacity and propagates the state diffs to replica nodes.
Prover Nodes: Nodes that generate proofs for transaction verification. They utilize specialized hardware such as GPUs, FPGAs, or ASICs to generate proofs for sequencer execution results.
Full Nodes: Responsible for complete state verification and storage. They store the entire blockchain state and re-execute all transactions to ensure data integrity.
Replica Nodes: Receive state diff from sequencer nodes and update state values in local environments. They verify states like full nodes but don't re-execute entire transactions like full nodes, instead relying on proofs generated by prover nodes to verify the validity of state increments received from sequencers.
Light Clients: Receive and store the latest state from replica nodes and full nodes, providing it to users. Mainly operated by application providers.
Source: MegaETH
The most unique component within MegaETH is the replica node. Replica nodes provide transactions with minimal verification to light clients for use by MegaETH dApps, enabling users to actually feel "real-time" performance. Without replica nodes, only state values that have undergone full re-execution from full nodes would be provided to applications, making it difficult to provide "perceptible real-time performance" regardless of how quickly the sequencer processes blocks due to full node bottlenecks.
This structure also brought about the very innovative result of practically eliminating block gas limits. In existing blockchains, gas limits were "hardware agreements" about the computational complexity that a single node had to handle. Since all full nodes had to re-execute all transactions within blocks, the network had to limit computational load to levels that even the lowest-specification nodes could handle. However, in MegaETH, computational verification is distributed to the prover node network, and replica nodes only receive state diffs and verify them through proofs, so individual node computational capacity no longer becomes a bottleneck for the entire network.
Through this, MegaETH achieved overwhelming performance improvements compared to typical EVM chains. Block gas limits increased 33-fold from 30 million gas to 1 billion gas, and deployable smart contract size expanded 21.3-fold from 24KB to 512KB. The computational load that a single transaction can handle is also 24.5 times larger than the entire block limit of existing chains. This enables complex computations such as fully on-chain 3D games that were considered impossible in fully on-chain environments.
2.2.2 Two Chain-Views Architecture
Another method MegaETH adopted to improve perceived performance is the two chain-views architecture, a system that operates two different block types in parallel.
Source: MegaETH
First, EVM blocks are traditional blocks generated at 1-second intervals for compatibility with the existing Ethereum ecosystem. These blocks possess complete metadata, allowing existing Ethereum infrastructure such as RPC calls, developer tools, and block explorers to integrate with MegaETH without complete system reconstruction.
On the other hand, Mini Blocks are blocks generated at very short intervals of about 10ms, eliminating overhead caused by traditional EVM block headers and containing only transaction results to propagate continuous state increments. MegaETH applications can receive millisecond-level confirmation for transactions by checking mini-block metadata, providing users with millisecond-level transaction processing experiences.
MegaETH's two chain-views structure is somewhat similar to methods that various blockchains have been actively adopting recently to provide fast user experiences, notably Solana's shreds, Hyperliquid's dual-block structure, and Base's Flashbots-based 200ms preconfirmation.
MegaETH's structure is similar to these but differs in that mini-blocks guarantee the same level of finality as EVM blocks and involve the same level of economic penalties for malicious behavior. This structure provides an experience as if transactions are being streamed in real-time, allowing users to experience revolutionary user experiences not available on existing chains, such as orders submitted on exchanges being immediately reflected in order books, or actions submitted as transactions in games being immediately reflected.
2.2.3 ZK Fraud Proof Mechanism
MegaETH seeks to enhance the efficiency of fraud proof challenges in existing optimistic rollups and provide better security through a hybrid approach that combines ZK and fraud proofs. It uses an interactive protocol where challengers and proposers find error points through a bisection method. In this process, both parties recursively narrow down the error point by dividing computational records in half, and ultimately determine fraud by re-executing errors at a single computational step on Ethereum. However, this approach has the disadvantage of requiring Ethereum transactions for each interaction, which can take several hours to days to resolve a single dispute, and malicious challengers can waste proposers' resources.
MegaETH aims to resolve these issues through RISC Zero's OP Kailua, which supports ZK-based fraud proof system. Within this system, fraud proofs can be submitted to Ethereum in a single transaction and have their validity verified immediately. Even in the worst case, it consumes realistic costs of about $100, making it resistant to the aforementioned griefing-type attacks. Additionally, it has significant time efficiency as entire disputes can be resolved within one hour. MegaETH's approach can greatly improve the speed of resolving fraud proof challenges, potentially reducing the time of state finalization to several hours, but maintains the typical 7-day challenge period of the other optimistic rollups for security considerations.
As mentioned earlier, MegaETH is currently collaborating with EigenDA for data availability, and the ZK fraud proof process through EigenDA can be described as follows:
The sequencer publishes block data to EigenDA and commits only a small reference to Ethereum.
EigenDA cryptographically guarantees proof generation, and sequencers cannot arbitrarily withhold data to avoid detection of malicious behavior.
All watchers can retrieve block data, reconstruct the entire block, and execute it through zkVM.
When fraud is detected, watchers generate concise ZK fraud proofs and submit them to Ethereum's verification contract, the sequencer gets slashed, and invalid proposals are rejected.
Through this ZK-based fraud proof system, MegaETH has built a cryptographically sound trust model that eliminates griefing risks, reduces finality time, and resolves disputes in an efficient and scalable manner.
2.2.4 RPC Performance Enhancement
Another core element MegaETH improved to implement real-time blockchain is RPC (Remote Procedure Call) optimization. In existing EVM chains, users used a polling method to repeatedly call for transaction receipt reception to confirm results after sending transactions. This method wasn't problematic in existing environments with slow block times of several seconds, but in environments like MegaETH where transactions are processed at millisecond levels, the polling design was both wasteful of resources and created processing delays for low-latency applications .
MegaETH developed and introduced new RPC method to solve this problem. This method combines existing transaction transmission (eth_sendRawTransaction) and receipt confirmation (eth_getTransactionReceipt) methods into one, having sequencers wait until transaction execution completion before returning executed transaction receipts directly instead of transaction hashes. This method completely eliminates delays from polling with unnecessary network calls to behaving like that of an API where request and response are done with 1 interaction.
MegaETH has enhanced the efficiency of RPC queries for the vast historical data it generates, improving both user and developer experiences. On its testnet, MegaETH processes over 1,000 transactions per second, generating data equivalent to a year of Ethereum data every five days. With existing RPCs, developers struggle to handle this large volume of data due to resource limitations, as queries that exceed the limit halt mid-query, return an error, and discard all previously completed work. This severely affects developer experience, especially for high-performance chains like MegaETH.
To solve this, MegaETH introduced paginated reads. Instead of returning an error when a query reaches resource limits, it provides the partial results processed along with a pointer showing where the query stopped. For instance, if a wallet searching for transactions over the last million blocks exhausts CPU time after 300,000 blocks, it immediately receives results from these blocks and can resume the query. This approach eliminates wasted work, reduces latency with fewer round trips, and significantly enhances the development experience for MegaETH applications handling large data volumes.
Through these RPC structure improvements, MegaETH improved real-time dApp development experiences while enhancing user experience delays for transaction processing to that of API calls.
MegaETH aims not just to implement real-time fast blockchain but to establish applications in its ecosystem that couldn't be implemented in other ecosystems using fast computational environments. To this end, the MegaETH team adopted a strategy of intensively supporting a small number of teams by opening their own accelerator program, MegaMafia.
MegaMafia selected 15 projects as the first cohort through strict selection criteria. These are projects that joined under the premise that real-time performance is essential, they must provide innovative use cases that couldn't be built before, and they must promise to build natively on MegaETH. MegaMafia founders live and work together with the MegaETH core team for one month, receiving intensive development and mentoring support from the MegaETH team during this period. This is an initial ecosystem construction method rarely seen in other chains, showing how much effort MegaETH is putting into initial ecosystem construction.
We’ll explore each of MegaMafia projects in the following section.
A notable aspect of MegaETH is its unique community building strategy. Starting from the investment stage, it chose the method closest to the community - MegaETH opened a $10 million community funding program through Echo, with over 3,200 investors participating. The investment value for MegaETH was at the same level as angel investors like Vitalik Buterin, allowing general investors to participate at an unusually low valuation.
Source: MegaETH
The second is "The Fluffle" collection, comprising 10,000 soulbound NFTs. MegaETH rejected the "fake communities" common in Web3 project farming, aiming to onboard individuals who could genuinely contribute to the ecosystem.
The first 5,000 were distributed to long-term NFT holders, ecosystem builders, app developers, early MegaETH supporters, and others likely to aid in ecosystem development or who had shown proven loyalty. The remaining 5,000 were allocated to each MegaMafia project for distribution within their respective communities.
Through this strategy, MegaETH fostered a community capable of making substantial initial contributions. They envisioned that newcomers, attracted by these contributions, would exert greater efforts to acquire The Fluffle.
MegaETH currently has 26 projects launched on testnet, and including projects scheduled for launch, a total of 56 projects are planned to onboard to MegaETH. This article examines representative projects in major areas like DeFi, infrastructure, games, AI, and social community services within the MegaETH ecosystem, focusing on MegaMafia projects, exploring how they make synergies with MegaETH.
The fastest-growing DeFi ecosystem today is the Central Limit Order Book (CLOB) based perpetual DEX (PerpDEX). These platforms are setting trends by replacing traditional Automated Market Maker (AMM) models, achieving high capital efficiency through precise price matching.
Implementing a fully on-chain CLOB was nearly impossible on existing chains due to high gas fees. Order creation, modification, cancellation, and matching require numerous transactions, making fulfillment challenging. Additionally, CLOB needs real-time price matching with high-frequency processing of large orders, but the long block generation times of existing chains were unsuitable.
MegaETH, with its high throughput and low latency, is ideal for fully on-chain CLOB implementation. DeFi projects looking to onboard MegaETH are primarily focusing on CLOB and high-frequency trading processing.
However, MegaETH's CLOB-based exchange projects differentiate themselves from other high-performance chain-based CLOBs by implementing various functions and connectivity beyond simple fast trade matching. Besides exchanges, various unique concept DeFi projects are being developed on MegaETH. This section introduces projects with particularly differentiated functions among MegaETH's DeFi projects.
4.1.1 GTE
Source: GTE
GTE is an integrated exchange that emerged to solve user experience problems where users had to access different platforms for the same token: launchpads for token launches, DEXs for initial trading, and futures exchanges for strategic product management.
GTE enables users to manage entire token lifecycles within one platform through four components:
Token Launchpad: GTE implemented launchpads for fair token launches without developer front-running. 80% of token supply is traded on bonding curves, and when bonding prices are reached, liquidity pools are automatically deployed to GTE AMM with 20% supply burned.
AMM-based DEX: Tokens bonded from launchpads automatically become tradeable on GTE AMM, and are automatically added to CLOB platforms upon reaching sufficient maturity and market depth.
Spot and Perpetual CLOB: Provides CEX-level liquidity and advanced trading features for mature assets. GTE implemented price-time priority matching through MegaETH's high performance.
Optimal Price Aggregator: Ensures optimal trade execution across GTE's AMM, CLOB, and the entire MegaETH ecosystem. Accessible through both programmatic integration and frontend interfaces to provide optimal prices for developers and general users.
GTE aims to support trading faster than Hyperliquid, approaching Web2 centralized exchange performance based on MegaETH's low latency, and seeks to build a true "on-chain Binance" by resolving issues like excessive listing fees charged by existing CEXs.
4.1.2 Valhalla
Source: Valhalla
Valhalla is a fully on-chain trading platform being developed by Three Sigma, also well-known as a security research firm, aiming to provide integrated user experiences by combining futures/spot/lending into one platform.
Valhalla implemented CLOB-based order matching systems using MegaETH's low latency and provides additional functions including:
Atomic Funding Farming: Funding fee farming means holding short positions equal to spot holdings to receive funding fees paid to short positions. Existing DEXs had risks of price movements due to time differences between spot purchases and short position opening, but Valhalla uses Flash Loans to execute both trades completely simultaneously, eliminating such risks.
Integrated Risk Management System: Allows position management, liquidation, and margin adjustment processing in single transactions.
Position Collateral: Maximizes capital efficiency by enabling immediate use of unrealized profits from existing positions as collateral for new positions.
Complete Integration between Futures/Spot/Lending: Valhalla operates within integrated frameworks in MegaETH, providing comparative advantages over Hyperliquid's bridging delays due to separated exchange and EVM environments.
Private Trading Support: Unlike other PerpDEXs forcing position disclosure through transparent order books, Valhalla provides flexibility for users to choose private or verifiable public trading based on strategy.
4.1.3 World Capital Markets (formerly Teko)
Source: World Capital Markets
World Capital Markets (WCM) is an exchange platform under development aiming to integrate MegaETH's DeFi platforms into one, providing users with new arbitrage opportunities and high capital efficiency. They drew motivation from the legendary quant fund LTCM (Long Term Capital Management), which dominated 5% of global markets in 1998 before eventual collapse. Just as LTCM dominated markets with Nobel laureates using Black-Scholes option pricing formulas, WCM claims to have found mathematical solutions for cryptocurrency lending and futures rates, seeking to implement this in exchange form.
WCM's biggest differentiation is undercollateralized lending. Existing DeFi lending platforms mostly use overcollateralization methods requiring collateral deposits with greater current value than loans due to cryptocurrency price volatility and user credit measurement implementation problems. Therefore, Web3's overcollateralized lending have relatively lower capital efficiency compared to Web2's credit-backed lending. WCM aims to maximize user capital efficiency by utilizing MegaETH ecosystem DeFi platforms. WCM real-time manages all spot/futures/lending positions users build within the MegaETH ecosystem, immediately offsetting losses from one position with profits from another, enabling users to receive loans using spot collateral and currently built positions as collateral.
Additionally, WCM provides functions enabling additional margin farming through lending position construction. For example, if users borrow $90 worth of ETH using $10 spot as collateral, WCM simultaneously builds equivalent ETH short positions enabling users to earn funding fee profits.
This structure requires very delicate risk management as it accumulates leverage in multiple stages. WCM seeks to solve this through “microliquidations.” Using MegaETH's millisecond block generation times, WCM executes partial liquidations in very small units immediately when user lending positions become risky. While existing systems liquidated entire positions at once causing large losses, WCM gradually liquidates only necessary amounts immediately upon risk detection, maximally protecting both lender and borrower assets.
Through this structure, WCM exposes general users to market arbitrage opportunities called "the only free lunch in finance," holding long-term visions of becoming hubs for all Web3 lending markets as arbitrage opportunities compress.
4.1.4 Avon Protocol
Avon Protocol points out the flexibility limitations of existing pool-based lending protocols that only support lending products with predetermined interest rates, and presents a CLOB-based matching system as a solution that allows borrowers and liquidity providers to directly define conditions. Liquidity providers deposit assets into curated pools that operate programmable strategies through smart contracts. Pool managers can present various conditions on the order book including interest rates, LTV ratios, and repayment terms, while users can review multiple conditions disclosed on the order book and borrow under the most favorable terms for them. To illustrate with a simple example, liquidity manager A of an ETH-USDC pool could make an order with specific conditions such as "1,000 USDC available for lending with ETH collateral at 3% interest rate and 85% LTV," and users can take it to secure a loan. This CLOB-based matching system is considered far more suitable than existing AMMs for implementing lending products that has multi-dimensional conditions in realistic scenarios.
Systems like Avon Protocol requiring real-time matching and settlement of complex conditions set by borrowers and depositors require very low latency and large-volume data processing, making DeFi lending products operate in relatively non-competitive environments. Avon Protocol enables various lending protocols to competitively provide products to users based on MegaETH's high throughput and low latency, expected to enable MegaETH ecosystem users to receive better lending conditions.
4.1.5 Euphoria
Source: @zacxbt
Euphoria is a mobile game with simple UI, which divides charts into rectangular grids, allowing users to bet on sections where they expect charts to be positioned in the future through taps. Euphoria aims to transform boring and pressuring derivatives trading into easy tap game forms, providing lighter experiences to current "TikTok generation."
While Euphoria appears to have lower implementation difficulty as a simpler game compared to other projects, it's very difficult to implement without MegaETH's real-time environment. The game Euphoria implements is like real-time matching of extremely short-term options to multiple users. This requires real-time asset price reflection of underlying asset, updating expected rewards for each grid section, and immediate prize payments upon user wins/losses. Delays in this process would severely degrade user experience, requiring chains with very low latency like MegaETH for fully on-chain implementation.
4.1.6 Noise
Source: Noise
Noise is a unique project departing from traditional futures trading betting on token price rises/falls, trading "mindshare." Mindshare is an indicator relatively showing how much attention projects receive in crypto communities, with more mentioned projects rated higher regardless of positive/negative sentiment.
Since mindshare moves differently from token prices, users can employ unique strategies through Noise. For example, when project token prices plummet, community mentions increase, making long positions on mindshare potentially advantageous.
Noise aggregates Web3-related posts from X through partnerships with Kaito, reflecting them in mindshare scores immediately reflected in user unrealized profits. Noise's implementation method would be nearly impossible to operate fully on-chain without chains with very low latency like MegaETH. Unlike prediction markets like Polymarket based on specific events, Noise requires continuous data processing, and mindshare typically has greater volatility than token prices, requiring very low latency for stable position management for each user.
4.1.7 Cap
Source: Cap
Cap is the sole stablecoin project within MegaMafia, addressing the centralization issues present in existing yield-bearing stablecoins. These stablecoins typically generate profits through investment strategies set by singular teams or governance systems, distributing gains to holders. However, users lack clear recourse if these teams or governance bodies become corrupt, and entire protocols are at risk when specific strategies lose profitability due to market changes.
Cap aims to solve these problems by implementing code-level, verifiable security. It utilizes Ethereum-based restaking protocol EigenLayer's Autonomous Verifiable Services (AVS) to ensure reliability and transparency.
Cap’s constituents are classified into three categories:
Users: Deposit assets to Cap and receive yield-bearing stablecoins as certificates, earning interests. They can withdraw their deposited assets later using these stablecoins.
Operators: Entities that generate profits for user payments using capital from restakers. They include financial institutions like banks, high-frequency trading companies, and market makers, all subject to regulations. Operators receive performance-based incentives and must surpass the basic yields set by Cap. This competitive environment encourages each operator to maximize yields.
EigenLayer Restakers: Serving as Cap's security layer, restakers closely monitor operator behavior and allocate capital based on performance evaluations. If operators engage in high-risk strategies that result in losses or commit malicious acts, the restaker's collateral is slashed. This slashed collateral is used to recover losses caused by operators. Restakers earn a share of the yields generated by operators as incentives.
Cap's structure minimizes risks to user-deposited assets by establishing restakers as decentralized guarantors. Additionally, Cap places no restrictions on how operators generate profits, operating under the assumption that restakers guarantee these operators. This setup exposes users to a variety of strategies across Web2 and Web3, including traditional financial products, MEV, and RWA. Users can thus access optimal rates, making Cap's offerings very attractive.
Cap will serve as a liquidity gateway between MegaETH and Ethereum, through collateral deposits on Ethereum and stablecoin issuance on MegaETH. It plans to quickly integrate with other DeFi projects in MegaETH to establish itself as MegaETH's core DeFi engine.
4.2.1 Pump Party
Source: Pump Party
Pump Party is a project designed to enhance user experiences by integrating on-chain game elements into live streaming platforms. Current platforms, such as Twitch, often lack features that actively engage viewers, offering only limited options like donations, simple point betting, or mission systems. Pump Party addresses these issues, aiming to create a more immersive streaming experience by combining a variety of on-chain mini-games with live broadcasts.
All games within Pump Party are implemented as on-chain smart contracts. These contracts record game results, prize distributions, and user leaderboards in a verifiable manner. Each game lasts about 10 minutes, which is relatively lengthy. However, with MegaETH's complex implementation and rapid block generation speeds, real-time recording of extensive interactions is possible, allowing for prize distributions to millions of wallets within seconds.
4.2.2 Sweep
Source: Sweep
Sweep is a project focused on integrating prediction markets into existing streaming platforms, in contrast to Pump Party, which is launching its own streaming service. Sweep allows viewers to place bets on live events, such as a streamer's gameplay rankings or the number of enemies defeated.
To implement platforms like Sweep on-chain, very fast on-chain environments are required. This is because hundreds of thousands of small bets need to be collected and processed in real time to calculate prize distributions accurately. Additionally, live streaming results must be submitted promptly to avoid discrepancies due to timing differences.
Sweep leverages MegaETH's fast on-chain environment and low gas fees to process user bets in real time, submit results, and distribute prizes to tens of thousands of wallets simultaneously. A key distinction of Sweep compared to Web2 streaming-based betting platforms is its ability to perform these processes on-chain in a verifiable manner.
4.2.3 Showdown
Source: Showdown
Showdown is a game crafted by top-ranked players of renowned turn-based card games like Hearthstone and Magic: The Gathering. It adds a variety of action cards to poker, creating multiple variables and an engaging experience. Players can develop strategies using decks with diverse characteristics such as Inventor, Gambler, Protector, Cheater, and Rebel.
Compared to other MegaETH projects, Showdown has relatively low on-chain dependency. Currently announced on-chain smart contract implementations include game prize pools, prediction markets, and reward distributions based on game results.
4.2.4 Autonomous World Engine
Source: Autonomous World Engine
Autonomous World Engine (AWE) is an open-world 3D game platform designed for creators. It enables effortless creation of 3D open worlds through a user-friendly drag-and-drop interface, facilitating content creation.
AWE implements and deploys all player actions, in-game objects, and their interactions as on-chain contracts. It offers detailed templates for each element, allowing creators unfamiliar with development to easily build games. These templates enable complex functions, such as multiplayer features, physics engine applications, and dynamic animations that respond to player interactions.
With AWE, creators can design unique experiences, including real-time on-chain interactions within 3D virtual worlds. It provides complete control over creations through the on-chain deployment of each open world.
4.2.5 Funes
Source: Funes
Funes aims to build online museums collecting, preserving, and curating 3D models of all human architecture. Called "Wikipedia of world monuments," Funes converts user-provided photo and video data into model data through 3D scanning, uploading them on-chain to build digital museums, seeking to provide virtual tourism and educational resources about architectural heritage.
Funes stores self-generated 3D models as on-chain data, requiring on-chain environments capable of quickly processing large data, making MegaETH one of the most suitable chains as Funes' infrastructure layer.
4.2.6 Nectar AI
Soucre: Nectar AI
Nectar AI is MegaMafia's sole AI project, allowing users to create uncensored and customizable AI companions using the latest AI models. Users can directly customize their virtual partners' appearances, personalities, and backgrounds for a highly personalized interaction experience. The goal is to provide conversation experiences that feel like real interactions, utilizing multimodal models capable of processing voice, text, and image inputs simultaneously.
Nectar AI also plans to enable users to port their created companion agents on-chain for monetization.
To date, over 500,000 companion agents have been created on Nectar AI's platform, engaging in a wide range of role-playing scenarios from medieval adventures to anime-like situations. Nectar is collaborating with AWE, a previously described 3D open-world creation platform, to develop games that allow users to interact with multiple Nectar AI companion agents simultaneously.
4.3.1 Lemonade
Source: Lemonade
Lemonade is an event and community management platform built on MegaETH. It addresses the inconvenience users face with existing platforms that are fragmented across ticketing, CRM, newsletters, token rewards, NFTs, and landing pages.
Lemonade aims to solve these issues with an integrated community management stack, covering everything from domain construction to event hosting. Users can create their own domains with custom brands and themes without needing development expertise, thanks to no-code development platforms. The platform provides tools to reward loyal community members with tokens for activities such as event attendance, ticket purchases, and check-ins, leveraging tokenized promise and time concepts.
Moreover, Lemonade seeks to automate processes like newsletter writing, event management, venue and speaker sourcing, marketing strategy development, and customer support using AI agents.
The platform is expanding through partnerships within the MegaETH ecosystem. It offers automated profits to users by handling stablecoin-based ticket sales, community funds, and CAP donations. It enables community token launches via GTE and implements token utility through proprietary no-code token managers. Additionally, it supports event loans through WCM's lending systems, significantly improving creators' access to capital.
Source: MegaETH
In examining each MegaMafia project, it's evident that MegaETH prioritizes projects that are novel and offer new user experiences over those that merely utilize MegaETH's on-chain environment. Currently, MegaETH is selecting the second cohort for MegaMafia following MegaMafia 1.0. The projects chosen will again adhere to the MegaETH team's stringent criteria.
Between April and June, more than 300 projects applied for MegaMafia 2.0. During this period, the MegaETH team shared unique insights gleaned from the application analysis through various posts.
The application analysis revealed that applicants exhibited traits characteristic of a new builder group dubbed the "Post-Infrastructure Generation" by the MegaETH team. This group operates under the assumption that the necessary technical infrastructure is either already in place or soon will be, allowing them to focus on creating user-centric applications. Applicants consistently highlighted their technical capabilities from the perspective of user benefits, prioritizing user experiences, such as "fast UX," over raw performance metrics.
One of the most notable traits among MegaMafia 2.0 applicants was their emphasis on user experience as the primary bottleneck for Web3 adoption, rather than technical issues. A significant 43% of applicants chose the question, "What is the biggest bottleneck for actual adoption of Web3 native apps?" This indicates that builders see user adoption challenges as more pressing than technical milestones. The MegaETH team highlighted one applicant's insightful critique: "The industry's belief that mass adoption will occur when the public understands the technology is mere self-rationalization. An obsession with 'public education' often serves as an excuse for poor UX. Web3 mass adoption will happen when the technology becomes invisible."
While MegaETH's development of a high-speed, low-latency blockchain is a remarkable innovation, the true impact comes from a few groundbreaking applications built upon it—something all blockchain projects desire. MegaMafia's elite apprenticeship approach positions MegaETH not merely as a project seeking user engagement through technological advances but as a foundational system for projects genuinely aiming to enhance user experiences.
