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Monad: The fast parallel Ethereum

Arya .ETH
Published On Nov 25, 2025 | Updated On Nov 25, 2025 | 14 min read
A glowing purple 3D symbol floats above a circular digital platform, illustrating an abstract monad concept in a futuristic sci-fi interface.
Monad, a performance-first EVM Layer 1 targeting 10,000+ TPS and sub-second finality with parallel execution and MonadBFT!

Monad is an EVM-equivalent Layer 1 that tries to make Ethereum-style applications run at the pace of modern parallel compute systems. Its core bet is that you should not have to abandon Solidity, Ethereum tooling, or the existing DeFi mental model to get sub-second finality and multi-thousand TPS. This review evaluates Monad through a Rango lens: how the chain works, whether the ecosystem is real enough to matter, and what its performance profile implies for cross-chain routing and liquidity aggregation. 

TL;DR

Monad is a high-throughput EVM Layer 1 designed to remove the sequential bottlenecks that keep most Ethereum-compatible chains in the low thousands of TPS. It combines a HotStuff-style BFT consensus, optimistic parallel EVM execution, and a custom storage and networking stack to deliver very fast blocks and near-instant finality. For Rango, the headline is simple: it is an EVM chain that looks like Ethereum to integrate, but behaves like a low-latency high-frequency venue in production. 

 

  • Monad is a performance-first, EVM-equivalent Layer 1 aimed at 10,000+ TPS with sub-second finality. The protocol keeps Ethereum bytecode and RPC semantics intact, so Solidity contracts, wallets, and infra can port with zero or near-zero refactors. The performance comes from re-architecting execution and consensus under the hood rather than changing the developer surface area. 

 

  • The chain uses MonadBFT consensus, parallel EVM execution, and asynchronous pipelining to hit low latency at scale. MonadBFT is derived from HotStuff and optimized for single-slot finality, so confirmations behave like “one block and done” even under load. Execution is optimistic and parallel, meaning independent transactions run simultaneously, and only conflicting ones are re-ordered, keeping results identical to Ethereum while scaling with CPU cores. 

 

  • Monad was founded by ex-Jump Trading low-latency engineers and is organized around Category Labs plus the Monad Foundation. The founders’ background in high-frequency systems shows up in the emphasis on pipeline efficiency, storage throughput, and fast block propagation. Category Labs leads protocol R&D while the Foundation manages ecosystem growth and decentralization, which is the standard L1 structure for long-term governance and grants. 

 

  • Public testnet has been live since February 19, 2025 with mainnet planned for late 2025. Testnet stats already show multi-billion transaction counts and stable sub-second blocks, which is unusually mature for a pre-mainnet L1. That makes it realistic for integrators to build now and flip endpoints at mainnet without a second integration cycle. 

 

  • Funding is deep at about $244M total, led by Dragonfly and Paradigm. The $19M seed was announced in 2023, and a $225M round closed in April 2024 with top-tier funds participating. This level of capitalization typically translates into heavy ecosystem incentives, infra partnerships, and exchange support around mainnet, which drives the early liquidity and bridge demand that aggregators thrive on.

Architecture and Performance

Monad is trying to solve a clear constraint in the EVM world: even if you increase gas limits and optimize clients, sequential execution caps throughput and stretches latency tails. The project’s approach is not to modify the EVM’s semantics, but to parallelize the pipeline that feeds those semantics. The result is a chain that preserves Ethereum determinism, ordering rules, and bytecode, while scaling execution and I/O like a modern multi-core system. 

MonadBFT Consensus

Monad uses MonadBFT, a proof-of-stake BFT protocol in the HotStuff family. The system is built for low message overhead and short rounds, which allows validators to finalize blocks quickly without waiting for extended confirmation depth. In practical terms, if a transaction lands in a block, it is final within roughly the next block interval, yielding a near-instant settlement feel. This is valuable for cross-chain systems because routing legs can assume finality almost immediately, reducing the need for conservative wait windows that degrade UX. 

Parallel EVM Execution by Optimistic Concurrency

Ethereum’s EVM is deterministic because ordering is fixed. Monad preserves fixed ordering but changes execution into optimistic parallelism. The runtime schedules transactions that are predicted to not conflict in state access, runs them simultaneously across cores, and commits them if the predicted access sets remain non-overlapping. If a conflict emerges, the runtime rolls back and re-executes the conflicting subset in a safe sequence, ensuring the final post-state matches Ethereum rules exactly. For DeFi, this means bursts of swaps and arbitrage can be processed without forcing every transaction to queue behind the slowest one, which is the key reason high-frequency markets can exist on Monad without changing contract logic. 

Asynchronous Pipelining

Most EVM chains tie consensus progress to execution completion. Monad decouples these stages using asynchronous pipelining. While execution workers process block N, consensus can already be voting and proposing block N+1, and storage can be committing state deltas in parallel. This structure removes idle gaps that are normally unavoidable when one stage becomes the critical path. The outcome is not only higher steady TPS, but also lower variance in block times, which is the thing integrators care about when they need predictable latency for quoting and bridging. 

 

A simple example of pipelining can be seen in the following image:

Pipelining Example
Pipelining laundry day. Top: Naive; Bottom: Pipelined.

MonadDB and High-throughput state I/O

At high TPS, CPU is not the whole story. The state database becomes the limiting factor, especially under parallel reads and writes. Monad introduces MonadDB, a custom Merkleized storage engine tuned for SSD throughput and low read amplification. The database is designed so that many execution threads can touch state simultaneously without turning storage into a serialization point. For validator operators, this shifts node requirements toward strong SSD and memory profiles, but it is also what makes sustained four-digit TPS realistic on commodity modern hardware rather than only in benchmarks. 

RaptorCast Networking and Fast Block Propagation

Execution speed is wasted if blocks propagate slowly. Monad’s networking layer, commonly referred to as RaptorCast, is built to keep propagation time low as validator counts grow. The design favors linear scalability and quick fan-out so that sub-second block intervals are not destabilized by gossip overhead. This pairs with MonadBFT to maintain rapid finality without relying on a tiny validator set. For the application layer, it creates a stable low-latency environment where price discovery and liquidation engines can operate with much tighter risk bounds. 

Why this Architecture Matters to EVM dApps

The important synthesis is that none of these components require developers to think differently. Contracts are still EVM bytecode. Calls are still standard ABI calls. Nodes still expose JSON-RPC like Ethereum. So the scaling comes from the chain’s internal pipeline, not from pushing complexity onto dApps. That is a strong fit for Rango, because we can add Monad as another EVM endpoint while benefiting from a new high-performance venue that can support dense DeFi activity. 

Founders and Organization

Monad was founded in 2022 by Keone Hon, James Hunsaker, and Eunice Giarta. The founding team has deep systems backgrounds from Jump Trading and other low-latency hardware and software environments. Their professional history explains the chain’s preference for pipelining, speculative concurrency, and careful I/O optimization. The core development entity began as Monad Labs in New York, and in late 2024 it rebranded its protocol R&D arm to Category Labs

 

In December 2024, the project formalized a two-entity structure. Category Labs continues to build the protocol and client stack under James Hunsaker’s leadership. The newly formed Monad Foundation oversees ecosystem development, decentralization, and community growth, with Keone Hon and Eunice Giarta moving into Foundation leadership roles. This split matters because it creates a neutral steward for grants and governance, and also clarifies where integrators should look for ecosystem and partnership coordination.

Network Stage

Monad is no longer an early research chain. It is in an advanced public testnet phase, and the ecosystem is already using it. The stage matters for Rango because we are supporting this fast Layerv1 blockchain from day 1. 

 

  • Public testnet is live since February 19, 2025 and is processing large-scale activity. Multiple explorers show multi-billion total transactions and stable block production at sub-second intervals, which indicates the core performance path is already running in the open. The testnet is open to wallets, dApps, infra providers, and end users, so the behavior we see is closer to real load than to internal benchmarking. 

 

  • Mainnet is planned for late November, and we are going to support it from day 1 when it launches publicly. With airdrop announcement in late October, anticipation of the mainnet launch is very soon is high. 

 

  • Developer tooling is effectively mainnet-grade already. Standard EVM workflows function normally, including Solidity deployments, Metamask style RPC connections, and common indexers. For integrators, this allows a build-now strategy where testnet endpoints can be swapped to mainnet with minimal deltas beyond gas and chain ID adjustments.

Funding and Investors

Monad’s capital base is one of its clearest signals of seriousness. In L1 land, the size, quality, and timing of raises directly affect ecosystem velocity, infra coverage, and liquidity bootstrapping. Monad’s funding profile implies a strong go-to-market cycle around mainnet, which is the moment when cross-chain volume spikes. 

 

  • Seed round in 2023 raised $19M led by Dragonfly Capital. The seed was announced as a foundational round to build a high-performance EVM Layer 1, and it included a broad syndicate of crypto funds and angels. This round financed early devnets and the first full client implementations, and it validated the core thesis before any public network existed. 

 

  • Series round in April 2024 raised $225M led by Paradigm, bringing total capital to about $244M. The raise was widely covered as one of the largest infrastructure rounds of the year, with participants including Coinbase Ventures, Electric Capital, and Greenoaks. That scale gives Monad plenty of runways for validator incentives, builder grants, exchange listings, and post-launch liquidity programs, which directly drives activity on new chains. 

 

  • The investor mix suggests a long-horizon infrastructure bet, not a short hype cycle. Paradigm and Dragonfly have a track record of backing base-layer platforms they expect to mature into multi-year ecosystems. Historically, chains with this kind of backing lean hard into early DeFi incentives and deep infra partnerships, which increases the probability of real on-chain liquidity and meaningful bridge flows on day one.

Ecosystem Projects and dApps

Even before mainnet, Monad is cultivating a performance-native application layer rather than only relying on ports. That matters because aggregator quality depends on the density of liquidity venues and the diversity of user intent. A chain that launches with only a couple of AMMs is not interesting to route across. Monad is shaping up to avoid that pitfall. 

 

  • DeFi is the ecosystem centerpiece, with venues that explicitly exploit low latency. Multiple teams are building AMMs, order books, and perp stacks on Monad testnet, attempting structures that usually require high throughput to feel usable. The early presence of these primitives implies that at mainnet, we will see both spot and derivatives liquidity arriving quickly, which creates a rich routing graph for Rango. 

 

  • Aggregation and blue-chip EVM apps are already testing the waters. Uniswap has enabled Monad testnet in its official interface, which is a strong compatibility and ecosystem-confidence signal. Native aggregators are also emerging on Monad testnet, suggesting that users will expect multi-venue routing on this chain from the start; a value that we, Rango Exchange, are providing for you from the first day of launch. 

 

  • Infra and cross-chain plumbing is being installed ahead of launch. Public RPC and explorer support is already live, and the presence of Foundation programs like Monad Madness signals ongoing onboarding of new teams. When a chain reaches this infra threshold in testnet, it usually means mainnet will open with functioning bridges, oracles, and indexers rather than waiting months for the basics. That dramatically reduces integration risk for cross-chain workflows.

Network Activity and Usage Metrics

Monad’s public testnet activity is unusually high for a pre-mainnet network. Explorer data indicates billions of total transactions and consistent high daily throughput windows. While some of that is driven by testnet incentive loops and automated participation, the magnitude still tells us something important: the chain is not failing under load, and its performance goals are being exercised outside a lab. 

 

  • Throughput and stability. Public explorer snapshots show sustained sub-second block times and ongoing transaction processing with healthy success rates. This is the key variable for DeFi market quality. When block intervals are short and predictable, order book updates, liquidation engines, and arbitrage loops tighten, which increases volume and liquidity depth. It also lowers the latency penalty of doing cross-chain routing, because the destination leg clears quickly enough to make atomic or near-atomic UX plausible.  

 

  • Testnet scale as a readiness proxy. A chain that can survive multi-million daily transactions in testnet without major instability is much more likely to handle incentive-driven surges on mainnet. Monad’s explorer totals already sit in the multi-billion range, which means the client stack has been iterated in public under real adversarial conditions. This is not just about raw TPS. It is about having a stable, observable, and debuggable network with mature tooling, which is what integrators need for production routing and bridge monitoring.  

 

  • What mainnet likely looks like. Given the funding runway and the current builder funnel, the mainnet phase should start with a strong DeFi and cross-chain pull. New L1s with large war chests frequently launch with liquidity incentives and user distribution campaigns, which typically cause a rapid bridge-in event, a DEX volume spike, and a long tail of retained activity. Since Monad’s design targets high-interaction apps, it is more likely than most EVM chains to maintain a high baseline after the initial rush rather than collapsing into inactivity. 

Conclusion

Monad occupies a rare position among upcoming Layer 1s. It offers a clear performance leap without forcing the ecosystem to abandon the EVM, and it has the financial and organizational scaffolding to translate technology into a real app layer. Parallel execution, pipelined consensus, and an optimized state engine create a low-latency environment that makes advanced DeFi structures viable on an EVM chain. The public testnet has already been stress-tested at scale, and infrastructure and ecosystem programs indicate mainnet will not launch into a vacuum. 

Resources and Further Readings

Frequently asked questions

Check out most commonly asked questions, addressed based on community needs. Can't find what you are looking for?
Contact us, our friendly support helps!

Is Monad compatible with existing Ethereum tooling and smart contracts?

Yes. Monad is fully EVM-equivalent, meaning Solidity contracts, Ethereum RPCs, wallets like MetaMask, and indexing tools work without modification. Performance gains come from the underlying pipeline, not from developer-facing changes.

How does Monad achieve parallel execution without breaking determinism?

Monad uses optimistic concurrency: it predicts non-overlapping state access, executes transactions in parallel, and replays only the conflicting subset. Final results match Ethereum’s sequential semantics exactly.

What does Monad’s performance mean for DeFi protocols and aggregators?

Sub-second finality, predictable block times, and multi-threaded execution enable faster price discovery, tighter arbitrage, and high-frequency trading, all of which improve routing quality and liquidity efficiency for aggregators like Rango.