Ethereum

Gas Abstraction is an infrastructure mechanism designed to reduce the complexity of blockchain interactions. Its core goal is to allow users to complete transactions without directly managing on-chain gas payments. Through designs such as Open Gas, Account Abstraction, and realtime blockspace coordination, ETHGas attempts to create a more seamless Ethereum interaction experience. Compared with the traditional Ethereum Gas model, Gas Abstraction places greater emphasis on application-layer sponsorship, unified fee management, and realtime transaction execution. It is also regarded as one of the key infrastructure directions for the next generation of on-chain user experience.

ETHGas’s Pre-confirmation mechanism is an infrastructure design intended to improve Ethereum realtime transaction efficiency by allowing transactions to receive early execution confirmation before they are formally written into a block. Compared with the traditional Ethereum model, which relies only on final on-chain confirmation, Pre-confirmation can reduce transaction waiting time and improve the realtime nature of on-chain interactions. ETHGas combines Pre-confirmation with blockspace markets, Builder coordination, and realtime execution mechanisms to explore a new transaction execution structure under the direction of “Realtime Ethereum.”

ETHGas (GWEI) is an infrastructure protocol built around Ethereum Realtime Blockspace. It aims to improve on-chain transaction efficiency and lower the barrier to entry for users through Pre-confirmation, Gas abstraction, and blockspace market mechanisms. As transaction demand on the Ethereum network continues to grow, ETHGas seeks to optimize Ethereum’s execution efficiency and interaction experience through realtime block resource scheduling and future blockspace trading. Concepts such as Realtime Ethereum, Open Gas, and Blockspace Market are also becoming new directions in the development of on-chain infrastructure.

Algorand (ALGO) is a high performance Layer1 blockchain built on the Pure Proof of Stake (PPoS) mechanism. It is mainly used to support payments, smart contracts, digital asset issuance, and financial grade on chain applications. As the blockchain industry gradually moves into DeFi, RWA, and enterprise financial infrastructure, Algorand is widely used in on chain scenarios that require high throughput, low latency, and instant finality. Its core feature is the use of a randomized consensus mechanism and fork free structure to seek a balance among security, scalability, and decentralization.

TAC converts TON user requests into cross-chain messages that can be executed in an EVM environment through the TON Adapter, while the Sequencer network handles verification, ordering, and execution coordination.

The TAC token is the native asset of the TAC network. It is mainly used for EVM gas payments, validator staking, governance participation, ecosystem incentives, and economic settlement in cross-chain execution.

TAC (TAC) is an EVM execution network built for the Telegram and TON ecosystems. Its core purpose is to allow TON users to access Ethereum applications directly through a cross-chain messaging mechanism.

As the Ethereum Layer 2 ecosystem expands rapidly, liquidity fragmentation and the complexity of cross-chain operations have become new challenges. The Ethereum Economic Zone (EEZ) is a technical framework designed to address these specific issues. In this article, you'll learn how EEZ works, its core technologies, and how it drives the vision of One Ethereum.

Fluent is a Layer 2 network developed on Ethereum, utilizing a Blended Execution architecture to allow applications from various virtual machines to run seamlessly on a single on-chain network.

Sonic is a high performance Layer 1 blockchain protocol designed to deliver extremely high transaction throughput and instant finality. As decentralized applications increasingly demand real time interaction, Sonic achieves processing capacity of more than 10,000 TPS and confirmation speeds of around 0.8 seconds through its core Sonic technology stack, which includes the Carmen database and an optimized EVM execution layer. As a major technological leap for the Fantom ecosystem, it is fully compatible with the Ethereum development environment and addresses the scalability and storage efficiency bottlenecks that have long limited traditional blockchains through a rebuilt underlying architecture.

MegaETH's primary use cases center on on-chain services that demand high speed, concurrent processing, and real-time feedback, including high-frequency trading, blockchain game interactions, and social applications.

MEGA is the native token of the MegaETH network. Its main uses include paying on-chain trading fees, incentivizing network participants, supporting ecosystem growth, and enabling governance and staking functionalities.

MegaETH is an Ethereum scaling network engineered for high-performance on-chain applications, prioritizing faster trade execution, greater system throughput, and an enhanced user experience.

Somnia and Monad are two of the most important representatives in the parallel EVM sector. Both aim to improve transaction throughput, but they take noticeably different technical paths. Monad relies mainly on Optimistic Parallel Execution and deferred execution to achieve 10,000 TPS while preserving Ethereum compatibility. Somnia, by contrast, performs a surgical reconstruction of the storage layer through its self-developed IceDB storage engine, combined with a multithreaded parallel mechanism designed to support industrial-grade workloads above 1,000,000 TPS. In simple terms, Monad optimizes the “ordering and processing” of execution flow, while Somnia removes the physical bottleneck of storage I/O at its root.

The technical core behind Somnia’s million-scale TPS lies in its low-level reconstruction of the EVM stack, mainly through the IceDB storage engine and its parallel execution engine. IceDB is a custom database built specifically for blockchain systems. By optimizing the Sparse Merkle Tree, or SMT, structure and reducing disk I/O friction, it directly addresses the read and write bottlenecks that traditional databases, such as LevelDB, face when handling massive state data. Combined with Somnia’s multithreaded parallel execution engine, transactions that do not interfere with one another can be distributed across multiple CPU cores and processed simultaneously.