Why Monad Can Hit 10,000 TPS But Ethereum Still Dominates DeFi
A new Layer 1 blockchain claims to run 10,000 transactions per second while staying fully compatible with every smart contract ever written for Ethereum. That is not a modest claim. It sits at the center of one of the most active debates in blockchain development right now: does raw throughput actually win in decentralized finance, or does something else keep one chain on top? Understanding that tension tells you a lot about where the industry is heading.
TL;DR
- Monad achieves 10,000 TPS through parallel execution and pipelining, while remaining fully compatible with the Ethereum Virtual Machine.
- Ethereum’s dominance in DeFi comes from liquidity depth, developer trust, and composability, not raw speed alone.
- Monad matters most to developers building high-frequency applications, but migrating existing DeFi liquidity remains the harder problem to solve.
What Monad Actually Is, And How It Differs From Other EVM Chains
Monad is a Layer 1 blockchain built to execute transactions in parallel rather than sequentially. Most blockchains, including Ethereum (ETH), process one transaction after another in strict order. That keeps state consistent and prevents conflicts, but it also creates a hard ceiling on throughput.
Monad breaks that ceiling by borrowing a concept from database engineering called optimistic parallel execution. The chain speculatively executes many transactions at the same time, then checks afterward whether any two of them touched the same state. If they did not conflict, all results stand. If they did conflict, only the affected transactions are re-run in the correct order. The net effect is that the vast majority of transactions complete in parallel without any rollback.
> Monad’s approach is closer to how a modern database handles concurrent reads and writes than how a traditional blockchain processes a block.
Monad also uses a technique called pipelining, which separates the stages of block processing, consensus, execution, and storage, so they run concurrently rather than one after the other. A new block can begin consensus while the previous block is still being written to disk. That alone compounds the throughput gains from parallel execution.
The result, according to Monad’s own documentation at monad.xyz, is a theoretical ceiling of 10,000 transactions per second with one-second block times and single-slot finality.
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What EVM Compatibility Actually Means For Developers
The letters EVM stand for Ethereum Virtual Machine, the software environment that runs smart contracts on Ethereum. When a blockchain calls itself EVM-compatible, it means that code written in Solidity or Vyper for Ethereum will run on that chain with little or no modification.
This is a bigger deal than it sounds. The Ethereum developer ecosystem is the largest in cryptocurrency. Years of audited libraries, tooling, and security patterns exist specifically for the EVM. Chains like Avalanche (AVAX), BNB Chain, and Polygon have all attracted developers primarily because that compatibility lowered the barrier to porting existing code.
Monad takes compatibility further than most. It does not just accept the same bytecode. It preserves the exact same execution semantics, meaning a contract that behaves a particular way on Ethereum will behave identically on Monad. That includes edge cases in how the EVM handles gas, storage, and stack depth.
For a developer, this means the migration path from Ethereum to Monad is closer to a configuration change than a rewrite. Existing testing frameworks like Hardhat and Foundry work without modification. That lowers friction significantly for teams already operating in the Ethereum toolchain.
> Full EVM equivalence means Monad inherits every security audit, every library, and every developer habit built for Ethereum over the past decade.
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Why Ethereum Still Dominates DeFi Despite Its Speed Limits
Ethereum processes roughly 15 to 30 transactions per second on its base layer. That is somewhere between 300 and 700 times slower than what Monad claims. Yet as of June 2026, Ethereum holds the largest share of total value locked across DeFi protocols by a wide margin.
Speed is not what keeps Ethereum on top. Liquidity is.
DeFi protocols are most useful when they have deep liquidity. Deep liquidity makes swaps cheaper, borrowing markets more stable, and liquidations less damaging. Liquidity accumulates where users already are, and users concentrate where protocols already exist. It is a self-reinforcing cycle.
Ethereum also benefits from composability. Because so many protocols exist on the same chain, a single transaction can interact with multiple protocols in sequence without leaving the network. A user can borrow from one protocol, swap on another, and deposit into a third, all in one atomic transaction. That kind of chained interaction is harder to replicate on a newer chain with fewer protocols.
Finally, Ethereum carries institutional trust. Major regulated entities and large funds have compliance frameworks built around Ethereum specifically. That takes years to replicate and cannot be solved by a faster execution engine alone.
For Monad, this creates a classic bootstrapping problem. Speed attracts developers. Developers build protocols. Protocols attract users. Users bring liquidity. But until that liquidity reaches critical mass, the speed advantage is theoretical for most DeFi use cases.
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The Applications Where Monad’s Throughput Changes Everything
Not every DeFi use case is equally constrained by Ethereum’s speed. For simple token swaps on an automated market maker, 15 TPS is often sufficient. The bottleneck is usually gas cost, not raw throughput.
But several categories of application are genuinely blocked by low transaction throughput.
On-chain order books are the clearest example. A central limit order book requires thousands of order placements, cancellations, and matches per second to compete with off-chain alternatives. This is why most on-chain trading platforms use automated market makers instead, because order books do not work well at Ethereum’s native throughput. Monad’s 10,000 TPS opens the door to order books that could realistically compete with centralized exchanges.
High-frequency liquidation engines are another case. In lending protocols, liquidations must happen fast when collateral values drop. On Ethereum, block times of around 12 seconds create windows where positions can become insolvent before any liquidation fires. Faster finality tightens those windows and allows lending protocols to offer better collateralization ratios.
On-chain gaming and fully on-chain applications also fall into this category. Games that process player actions as transactions need throughput measured in thousands per second, not tens. Monad’s (MON) architecture makes this class of application economically viable at scale.
The common thread is that these applications require transaction throughput as a prerequisite, not as a nice-to-have. For them, Ethereum’s current base layer is a genuine blocker, not just a cost inconvenience.
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How Monad Compares To Other High-Throughput Chains In 2026
Monad is not the only project targeting Ethereum developers with a faster execution environment. Solana (SOL), Aptos, and Sui have all made throughput central to their pitch. Understanding where Monad sits in that landscape requires looking at the actual trade-offs.
Solana (SOL) processes roughly 3,000 to 5,000 non-vote transactions per second under typical load. It uses a different virtual machine entirely, the Sealevel parallel runtime, and a different programming model based on Rust. That means Ethereum developers must learn a new language and framework to build on Solana. The performance is real, but the migration cost is high.
Aptos (APT) and Sui (SUI) use the Move programming language, also derived from a research project at Meta. Again, the execution models are fast, but neither chain is EVM-compatible. Moving a battle-tested Solidity protocol to Move requires a full rewrite and re-audit.
Monad’s differentiation is that it delivers Solana-class throughput without asking developers to abandon the EVM. That is a narrower claim than “fastest chain,” but it is arguably the more commercially relevant one given where most existing protocol code lives.
The honest caveat is that Monad’s 10,000 TPS figure reflects benchmark conditions. Real-world throughput depends on the actual distribution of transaction types, the degree of state contention between them, and network conditions. Chains routinely achieve lower throughput in production than in benchmarks. Monad’s architecture is sound, but the live performance record is still building.
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Who Actually Benefits From Building On Monad Right Now
The answer depends heavily on what you are building and where your users already are.
If you are a DeFi protocol with significant existing liquidity on Ethereum, the calculus is unfavorable for a full migration. Your users are on Ethereum. Your integrations are on Ethereum. Your security audits are Ethereum-specific. Monad’s speed advantage does not immediately translate into better outcomes for your existing user base, because the bottleneck for most large DeFi protocols is liquidity depth, not block throughput.
If you are a new team building a protocol from scratch, Monad is a genuinely compelling starting point. You get Ethereum’s tooling and security model without Ethereum’s throughput ceiling. You can target application categories that are impossible at 15 TPS. And you enter an ecosystem where early protocols can still achieve significant visibility.
If you are a developer building infrastructure, particularly tooling, bridges, or oracles, Monad’s growth creates real demand. Every new Layer 1 with meaningful activity needs a full stack of supporting infrastructure, and that infrastructure is where durable value tends to accumulate.
For end users and traders, Monad’s relevance is tied to what protocols ultimately launch and find adoption there. Speed at the chain level translates into user experience only when the applications on top of it are built to take advantage of it.
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Conclusion
Monad and Ethereum are solving different problems, even though they share the same execution environment. Ethereum’s dominance in DeFi is a product of accumulated liquidity, composability, and institutional trust that took years to build. Those advantages do not evaporate because a faster chain enters the market.
What Monad does is open a new design space. Applications that were architecturally impossible at Ethereum’s native throughput, full on-chain order books, tightly timed liquidation engines, real-time on-chain games, become feasible at 10,000 TPS. The EVM compatibility removes the single largest barrier to developer adoption, which is the cost of learning a new execution model.
The question is not whether Monad is faster than Ethereum. It is. The question is whether throughput is the binding constraint for the applications that will define the next wave of DeFi. For some of them, it clearly is. For others, the harder problem remains attracting the liquidity that makes any protocol worth using. Both chains will likely coexist, each serving the use cases where their specific trade-offs are the best fit.
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