Why L1 Scalability Is Making a Surprising Comeback

Rollups are only as scalable as their DA layer. Ethereum's ~80 KB/s blob throughput is a hard cap for the entire L2 ecosystem, creating a shared ceiling.

• Celestia and EigenDA emerged to solve this, proving demand for high-throughput DA.
• New L1s like Monad and Sei are internalizing this lesson, building >1 GB/s DA layers natively.
• This eliminates the cross-chain consensus overhead, the primary latency killer in modular stacks.

Ethereum's sequential execution is a legacy constraint. Modern L1s treat state access as the key problem.

• Solana's Sealevel and Aptos' Block-STM pioneered this, enabling ~10k TPS.
• Monad is pushing it further with pipelining and superscalar execution, targeting >10k TPS of real EVM-compatible throughput.
• This makes complex DeFi composability (think Uniswap, Aave) radically cheaper and faster without L2 fragmentation.

The EVM is a one-size-fits-all compromise. New L1s are optimizing the entire stack for specific use cases.

• Fuel uses a UTXO-based parallel VM for maximal throughput in payments and swaps.
• Berachain's Polaris EVM is built around liquid staking and DeFi primitives.
• Sui's Move language and Narwhal-Bullshark consensus are optimized for managing rich on-chain assets.
• This vertical integration allows for deeper optimizations than a generic L2 can achieve.

The Problem: EVM sequential execution is a fundamental bottleneck.\nThe Solution: Monad introduces parallel execution and a novel state database (MonadDB) to unlock hardware-level throughput.\n- 10,000+ TPS target via parallel transaction processing.\n- Full bytecode compatibility with Ethereum, enabling seamless migration of dApps like Uniswap and Aave.\n- Superscalar pipelining separates execution, consensus, and mempool propagation for optimal latency.

The Problem: General-purpose chains are inefficient for high-frequency trading, causing front-running and high latency.\nThe Solution: Sei v2 implements the first parallelized EVM within the Cosmos ecosystem, optimized for order-book DEXs.\n- ~500ms block times with instant finality via Twin-Turbo Consensus.\n- Native order-matching engine and front-running prevention (FBA) built into the chain layer.\n- Interoperability via IBC, connecting to a $60B+ Cosmos ecosystem.

The Problem: Global state contention (e.g., popular NFTs) serializes transactions.\nThe Solution: The Move VM with object-centric data model allows independent transactions to process in parallel.\n- Horizontal scalability: Throughput increases with additional validators.\n- ~100k TPS in controlled benchmarks for simple payments.\n- Formally verified safety via Move's resource-oriented programming, reducing DeFi exploit surface.

The Problem: Proving high throughput with low cost at scale is an unsolved engineering challenge.\nThe Solution: Solana's monolithic architecture with Proof of History (PoH) provides a verifiable clock, enabling ~400ms block times.\n- Historical Proof: $4B+ in stablecoin volume and ~2,500 TPS sustained under real load.\n- Hardware-driven roadmap: Firedancer client aims for 1M+ TPS by optimizing network and execution layers.\n- Native fee markets per state component prevent network-wide congestion.

The Problem: Modular stacks (Rollups, Celestia, EigenDA) introduce fragmented liquidity and complex bridging.\nThe Solution: New L1s offer a unified security and liquidity layer, simplifying development.\n- Atomic Composability: All dApps share the same state and latency, unlike fragmented rollup ecosystems.\n- Developer Experience: One chain to deploy on, versus managing L2 sequencers, data availability, and bridging.\n- Economic Security: $1B+ staked in validator sets directly secures the chain, unlike modular security pooling.

The Problem: Blockchains lack native mechanisms to align validator incentives with ecosystem liquidity growth.\nThe Solution: Berachain's Proof-of-Liquidity consensus uses a tri-token model (BERA, BGT, HONEY) to stake liquidity instead of just tokens.\n- Liquidity-as-Security: Validators earn fees by providing liquidity to native DeFi pools.\n- EVM-compatible via Polaris, attracting existing tooling and developers.\n- Built-in DEX & stablecoin (HONEY) creates a flywheel for sustainable TVL growth from day one.

Splitting execution, settlement, and data availability across chains like Celestia, EigenDA, and Arbitrum creates capital inefficiency. Every hop adds latency and cost, killing UX for high-frequency DeFi.

• Problem: A user swap may need funds on 3+ chains, locking ~40% of capital in bridges.
• Solution: A performant monolithic L1 like Solana or Monad keeps assets and state unified, enabling sub-second atomic composability.

Cheap external DA from Celestia or Avail creates a critical liveness dependency. If the DA layer halts, so do all rollups built on it—a systemic risk.

• Problem: You've traded L1 security for a new, untested failure mode.
• Solution: Integrated DA/L1s like Ethereum (post-Danksharding) and Near offer stronger guarantees. New L1s are optimizing DA internally with data sharding and parallel execution.

The most innovative DeFi and on-chain games require tight, synchronous state updates across multiple protocols. This is impossible with 12-second block times or multi-chain fragmentation.

• Problem: Uniswap, Aave, and Friend.tech clones on slow chains lose their competitive edge.
• Solution: L1s with parallel execution (Solana SVM, Monad's MonadBFT) and ~200ms block times enable new application primitives, attracting the next wave of $10B+ TVL.

Ethereum's single-threaded EVM is a fundamental bottleneck. The next generation of L1s is adopting parallel execution engines derived from Aptos and Sui (MoveVM) and Solana (Sealevel).

• Problem: Sequential processing caps throughput at ~100 TPS for complex transactions.
• Solution: Monad (parallel EVM) and Sei (parallel CosmWasm) promise 10,000+ TPS for real-world dApps by utilizing modern hardware.