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In-Depth Analysis of Monad: How Parallel Execution and MonadBFT Build a High-Performance EVM Ecosystem
In the competition for underlying infrastructure in the crypto industry, there has long been a seemingly unsolvable dilemma: ensuring compatibility with the Ethereum Virtual Machine (EVM) to promote a thriving developer ecosystem often means sacrificing execution efficiency; whereas pursuing high throughput on non-EVM chains like Solana requires abandoning the large Solidity developer community and mature tooling. This trade-off between compatibility and performance constitutes the core strategic battleground for public blockchains.
Monad’s emergence attempts to offer a third solution to this dilemma. It does not build an entirely new Layer 1 architecture from scratch but is a bottom-up reconstruction based on the EVM standard, aiming to boost transaction processing capacity to a level comparable with high-performance non-EVM public chains without modifying a single line of Solidity code.
When EVM-compatible chains enter the “tens of thousands TPS” era
Monad is a fully EVM-compatible Layer 1 blockchain. According to its underlying design and community testing data, the network has demonstrated a theoretical processing capacity of over 10,000 transactions per second during its testnet phase. While this figure is still below Solana’s claimed ~65,000 TPS, it represents a magnitude leap over Ethereum’s baseline performance of about 15 TPS. More importantly, this performance boost is achieved while maintaining bytecode-level compatibility with EVM, meaning existing Ethereum decentralized applications can theoretically migrate with zero cost.
As of April 22, 2026, the native token MON of Monad traded at $0.03433 on the Gate platform, with a 24-hour trading volume of $3.07 million, and a daily price change of +5.83%. Its current circulating market cap is approximately $368 million, with a fully diluted valuation around $3.4 billion. Notably, its circulating supply accounts for only 10.83% of the total supply of 100 billion tokens, indicating an early-stage market supply structure.
From a funding frenzy to the final sprint before mainnet launch
Tracing Monad’s development trajectory, its technical narrative has consistently been accompanied by high market attention and capital deployment:
The “Super EVM” triad: three pillars of technology
Monad’s technical moat is not built on a single algorithm optimization but on the coordinated reconstruction of consensus mechanisms, execution layers, and network layers. The following is a breakdown of the three core components:
Parallel Execution: optimistic concurrency and conflict rollback
This is the core module for Monad’s performance enhancement. Traditionally, EVM processes transactions sequentially. Monad’s strategy is: assume transactions do not conflict and execute in parallel optimistically, then verify state consistency afterward. If conflicts are detected (e.g., two transactions modifying the same contract balance simultaneously), the system rolls back one and re-executes serially.
This design allows Monad to reuse a vast amount of Solidity codebase. In contrast, Solana’s Sealevel requires developers to explicitly declare state dependencies for parallelism, and Sui adopts an object-oriented UTXO model. Although extreme conflict scenarios may incur rollback overhead, Monad achieves frictionless migration while maintaining EVM compatibility.
MonadBFT: pipelined Byzantine Fault Tolerance
The consensus mechanism determines how the network agrees on transaction order. MonadBFT is an engineering-optimized variant based on HotStuff. Its key feature is the introduction of pipelining, decoupling and overlapping the four stages of block proposal, validation, pre-commit, and commit. This design significantly reduces finality latency even in the presence of malicious nodes, supporting higher block production frequency.
RaptorCast: solving the “broadcast storm” in Gossip protocol
In high TPS environments, bandwidth for propagating transactions across the network can become a hidden bottleneck. RaptorCast slices and layers transaction data for layered distribution. Nodes can participate in consensus without receiving the full network transaction pool copy, greatly lowering hardware and bandwidth requirements, making running full nodes and verifying the network more feasible for ordinary users.
Performance expectations and supply pressure game
Based on current crypto community discussions, market sentiment toward Monad is a complex mix of optimism and caution:
Industry impact analysis: EVM ecosystem’s internal competition and spillover
Monad’s emergence has significant structural implications for the infrastructure competition landscape in crypto:
Conclusion
Monad’s story reflects the core contradiction in current crypto infrastructure: rebalancing developer experience and user experience. In the past, users endured high costs and low speeds on Ethereum because developers hesitated to leave EVM. Monad aims to prove that both can be achieved simultaneously. As the April 24 unlock approaches and mainnet deployment progresses, market attention will shift from white papers to on-chain validation. For participants, stripping away marketing noise and focusing on real on-chain activity and fund retention will be key to assessing its long-term value.