The Core Problem: Why Ethereum Is Slow
Understanding Monad requires understanding why Ethereum is slow in the first place. The EVM executes transactions sequentially — one after another, in order. Every single transaction must be fully processed before the next one begins.
This is by design. Sequential execution guarantees determinism: every node on the network arrives at the exact same state after processing a block. It prevents the kind of race conditions that could corrupt the blockchain's state. The problem? It's fundamentally unscalable.
Consider a block with 200 transactions. On Ethereum, those 200 transactions are processed one at a time, even if 180 of them have nothing to do with each other. Sending ETH to your friend doesn't interact with someone else's Uniswap swap — yet the EVM waits for each to finish before starting the next.
Solana solved this with its Sealevel engine, which runs non-overlapping transactions in parallel. But Solana writes contracts in Rust, not Solidity. It uses a completely different runtime. Porting a dApp from Ethereum to Solana essentially means rewriting it from scratch.
Monad's thesis: parallel execution + EVM compatibility = the best of both worlds. Run Solidity smart contracts at speeds previously only possible on non-EVM chains.
How Monad's Parallel Execution Works
Monad introduces three key technical innovations that enable parallel EVM execution without sacrificing safety:
1. Optimistic Concurrency Control (OCC)
When a transaction arrives, Monad doesn't immediately lock state. Instead, it optimistically executes the transaction and records which parts of the state it read and wrote. This is called a read-set and write-set.
After optimistic execution, Monad checks for conflicts. If two transactions both tried to modify the same storage slot, one of them is re-executed with the updated value. If there are no conflicts, the results stand. This approach works because in practice, the vast majority of transactions in a block don't conflict with each other.
The cost of this approach is wasted work on conflicting transactions — but in benchmarks, conflict rates typically sit below 5%, making optimistic execution dramatically faster than sequential processing.
2. Deferred Execution
Traditional block production combines two steps: consensus (agreeing on transaction ordering) and execution (running the transactions and computing the new state). Ethereum does both sequentially, which means execution is on the critical path for block finalization.
Monad decouples them. Consensus happens first and fast — nodes agree on the order of transactions without executing them. Execution is then deferred and run in parallel after consensus completes. This architectural shift means consensus latency is independent of execution complexity.
3. Parallel Database (MonadDB)
State storage is a major bottleneck for any EVM chain. Ethereum's Patricia Merkle Tree was designed for proof of correctness, not speed. Monad replaces this with MonadDB, a custom database built on top of a parallel key-value store optimized for the access patterns of blockchain workloads.
MonadDB supports concurrent reads and writes, enabling multiple CPU cores to access state simultaneously. This is critical — without a parallel-friendly database, parallel execution stalls on state access.
Monad vs. Other L1s: A Speed Comparison
| Chain | Max TPS | Block Time | EVM Compatible? | Language |
|---|---|---|---|---|
| Ethereum L1 | ~15 | 12s | Yes (native) | Solidity |
| Monad | 10,000+ | ~1s | Yes (native) | Solidity |
| Solana | 65,000 | ~0.4s | No | Rust |
| Aptos | 160,000 | ~1s | No | Move |
| Sui | 120,000 | ~0.5s | No | Move |
| BNB Chain | ~2,200 | 3s | Yes (native) | Solidity |
| Polygon PoS | ~7,000 | 2s | Yes (native) | Solidity |
Monad occupies a unique position: it's the only chain that combines native EVM compatibility with 4-figure TPS at the base layer.
The MON Token: Economics and Distribution
- Total Supply: 100.68 billion MON
- Circulating Supply: ~11.8 billion MON (~11.7% of total)
- Fully Diluted Valuation: ~$1.9 billion
- Market Cap: ~$224 million
- All-Time High: $0.0488 (November 2025)
One notable factor: the gap between market cap ($224M) and FDV ($1.9B) is large. This means roughly 88% of the total token supply is still locked or yet to be released. Investors should be aware of future token unlock schedules.
MON is used for transaction fees, staking to secure the network, and governance.
The DeFi Opportunity on Monad
Why does 10,000 TPS matter? The killer app is DeFi at scale.
- Real-time liquidations: Collateral positions can be liquidated within milliseconds, significantly reducing bad debt risk for lending protocols.
- High-frequency DeFi: On-chain order books with millisecond-level updates, enabling CEX-like trading experiences without intermediaries.
- Mass multiplayer on-chain applications: Games, social protocols, and prediction markets that require thousands of concurrent state updates.
- Seamless migration: Existing Solidity contracts can be redeployed with minimal modifications.
Risks and Challenges
Execution Conflicts at Scale
Optimistic concurrency control works well when transactions rarely conflict. But during periods of extreme market stress — like a flash crash — thousands of transactions may simultaneously attempt to modify the same state. In these scenarios, parallel execution offers diminishing returns and may even be slower due to rollback overhead.
Decentralization vs. Performance
Running 10,000 TPS requires significant hardware. The minimum hardware requirements for a Monad validator node are substantially higher than Ethereum's. This could lead to fewer validators and higher centralization.
Token Inflation Pressure
With over 88% of the token supply still to be released, MON faces ongoing inflation pressure. The project's long-term value depends on whether real usage and fee revenue can offset inflationary supply expansion.
Bottom Line
Monad represents a technically rigorous attempt to solve one of crypto's oldest problems: how to have EVM compatibility and high throughput simultaneously. The parallel execution architecture is sound in theory, and early benchmarks are promising.
For developers, Monad is worth watching — it's one of the few chains where you can deploy your existing Solidity code and see it run orders of magnitude faster. For investors, the large FDV-to-market-cap ratio and competitive landscape suggest caution.
Not financial advice. Always DYOR.
Originally published on Crypto Brief
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