Monad scaling and the 200,000 TPS benchmark

High throughput and the $200 million incentive

Monad reached a 200,000 TPS benchmark during its devnet testing. This performance follows the recent completion of a $200 million testnet incentive program. My verdict is that Monad delivers on its high-performance promise. The network targets 10,000 sustained transactions per second. The testnet gas rate reached 500 million gas per second with a 150 million gas block limit. The system uses MON as the native token. Developers use Chain ID 10143 to add the Monad testnet to wallets like MetaMask or Phantom. The testnet allows builders to use familiar tools like Hardhat, Foundry, or Remix. Validators observe the same set of pending transactions in a shared mempool. This design helps DeFi protocols by reducing inconsistencies in how validators see transaction order. The testnet provides gas in MON via a faucet, while users track deployments on MonadScan or other block explorers. Developers use RPC endpoints from providers like Chainstack or QuickNode.

MonadBFT and RaptorCast

MonadBFT delivers two-round finality. Since rounds happen every 300 ms, finality occurs in 600 ms. Finality of block N occurs at the proposal of block N+2. MonadBFT uses pipelined consensus to produce a new block every round. This approach keeps block times short. MonadBFT also resists tail-forking. If a leader misses a round, the network collaborates to ensure the original proposal is restored. The Monad architecture uses a specialized messaging protocol called RaptorCast to divide blocks into smaller chunks, which validators then distribute across a two-level broadcast tree to ensure the network handles large data loads without massive upload bandwidth. MonadBFT is a modification of the HotStuff protocol that reduces the authentication rounds from three to two to increase performance. Communication is linear under normal circumstances. In a timeout scenario, communication becomes quadratic. Validators send timeout messages to each other if they do not receive a valid block. In RaptorCast, each chunk goes to one validator. That validator then sends the chunk to every other validator in the network. This two-level broadcast tree ensures message delivery occurs within 2x the longest hop. The network relies on 150 to 200 validators to secure the chain. These validators need a 16-core 4.5 GHz processor and 32 GB of RAM. A machine with 2x 2 TB SSDs and 300 Mbps bandwidth costs about $1500 to assemble.

Parallel execution and EVM compatibility

Monad uses optimistic parallel execution. It processes multiple non-conflicting transactions simultaneously. The system separates transaction ordering from execution through deferred execution. This design allows the network to maximize throughput while maintaining deterministic results. MonadDB handles parallel reads and writes to prevent storage bottlenecks. You already know how the EVM works, so focus on the implementation. Monad supports the Cancun fork with TSTORE, TLOAD, and MCOPY. The maximum contract size is 128 kb. This is much larger than the 24.5 kb limit on Ethereum. MonadDB uses asynchronous read and write operations to optimize data access, which prevents the bottlenecks found in traditional sequential databases. The network supports 19 wallets including MetaMask, Phantom, and OKX. The Monad client uses C++ for execution and Rust for consensus. The 200,000 TPS devnet benchmark shows massive potential, but the 150 to 200 validator count is small compared to Ethereum’s 1 million plus validators.

Will the 200,000 TPS devnet benchmark hold under the heavy load of the mainnet launch?