The term "Layer 1" shows up constantly in crypto conversations, usually paired with "Layer 2" or used to distinguish between different types of blockchains. But the classification isn't arbitrary marketing—it describes where settlement actually happens and which system holds ultimate responsibility for security and finality.
A Layer 1 blockchain is a base-layer protocol that processes and finalizes transactions independently, without relying on another blockchain for security or consensus. Bitcoin, Ethereum, Solana, and Cardano are all Layer 1 networks. The "Layer 1" designation matters because it tells you where the final source of truth lives—and what happens if that layer fails.
How Layer 1 Blockchains Work
A Layer 1 operates as a complete, self-contained system with three core responsibilities:
Transaction execution. The L1 processes transactions according to its rules—whether that's simple value transfers (Bitcoin) or complex smart contract execution (Ethereum). Every validator or miner runs the same software and independently verifies that transactions follow protocol rules.
Consensus and ordering. The L1 determines which transactions are valid, in what order they occurred, and which block becomes part of the canonical chain. This happens through a consensus mechanism—proof of work for Bitcoin, proof of stake for Ethereum, proof of history for Solana. The consensus layer is what prevents double-spending and ensures all nodes converge on the same state.
Settlement finality. Once an L1 includes a transaction in a block and that block achieves finality (probabilistic in Bitcoin, deterministic in Ethereum post-PoS), the transaction is settled. There's no higher authority to appeal to—the L1 is the final arbiter. This is why it's called the "base layer."
The key characteristic: an L1 doesn't outsource any of these responsibilities. It handles execution, consensus, and settlement internally. If you're using Bitcoin, Bitcoin validators finalize your transaction. If you're using Ethereum, Ethereum validators provide security. The chain itself is the trust anchor.
Where Constraints Live
Layer 1 blockchains face binding constraints that shape their design and performance:
The blockchain trilemma. L1s must balance three properties: decentralization (how many independent parties control the network), security (resistance to attacks), and scalability (transactions per second). Improving one typically means compromising another. Bitcoin prioritizes decentralization and security but processes ~7 transactions per second. Solana targets high throughput but requires expensive hardware that limits validator participation.
Consensus overhead. Every L1 transaction must be verified by thousands of independent nodes to maintain decentralization. This coordination takes time and computational resources—there's no way around it if you want global consensus without a trusted intermediary. The consensus mechanism choice determines the specific tradeoffs: proof of work requires energy expenditure, proof of stake requires capital lock-up, and all consensus models require network communication overhead.
State growth. As L1s process more transactions, their state (the current balance of all accounts, smart contract storage, transaction history) grows continuously. Validators must store and access this state to verify new transactions. Over time, hardware requirements increase, potentially reducing the number of participants who can afford to run full nodes. Ethereum's state is approaching 1TB—manageable now, but a long-term constraint.
Validator economics. L1s need enough validators to stay decentralized, but validators need sufficient revenue to cover costs. Transaction fees fund validator operations, but if fees are too high, users migrate to alternative systems. If fees are too low, validator participation may decline. Finding the economic equilibrium that keeps security strong while maintaining usability is an ongoing challenge.
These constraints aren't bugs—they're fundamental tradeoffs inherent to building decentralized systems where no single party controls the outcome.
What's Changing
Several structural shifts are altering how Layer 1s function:
Ethereum's rollup-centric roadmap. Ethereum has explicitly positioned itself as a settlement and data availability layer for Layer 2 rollups rather than trying to scale execution on L1. EIP-4844 (proto-danksharding) introduced blob transactions specifically to make L2 data posting cheaper. This represents a deliberate architectural choice—accept L1 execution constraints and scale through layered infrastructure.
Modular blockchain emergence. Projects like Celestia separate consensus and data availability from execution, allowing developers to build chains that use Celestia for data availability but handle execution independently. This challenges the monolithic L1 model where one chain does everything. The question isn't settled yet whether modular designs outperform integrated L1s.
Client diversity initiatives. After the Merge, Ethereum prioritizes having multiple independent client implementations to prevent a single bug from taking down the network. Solana is developing Firedancer as a second client. L1 resilience increasingly depends on software diversity, not just validator geographic distribution.
Alternative consensus models. Proof of history (Solana), federated Byzantine agreement (XRP), and delegated proof of stake (Cosmos) represent experiments in consensus design that make different tradeoffs than pure proof of work or stake. Whether these alternatives prove durable at scale remains an open question.
What Would Confirm L1 Resilience
Observable signals that an L1 is maintaining its core function:
Sustained decentralization metrics. Nakamoto coefficient (number of entities needed to control 33% or 51% of the network) remaining stable or improving. Validator count growth across diverse geographic regions. Full node counts staying healthy as state grows.
Consensus functioning through stress. L1s successfully processing high transaction volumes during network congestion without consensus failures, prolonged downtime, or forced manual intervention. Bitcoin and Ethereum have demonstrated this—blocks continue regardless of mempool size or fee levels.
Economic security scaling with value. As L1s secure more economic value (TVL, stablecoins, tokenized assets), validator revenue from fees or block rewards grows proportionally, maintaining incentive alignment without requiring artificially high inflation.
What Would Break or Invalidate the L1 Model
Signals that an L1 has fundamental problems:
Repeated consensus failures. If an L1 experiences frequent chain splits, requires manual validator coordination to restart, or suffers successful 51% attacks, its claim to being a reliable settlement layer breaks down.
Unsustainable economics. If validator participation collapses because revenue doesn't cover costs, or if only a handful of entities can afford to validate due to hardware requirements, the decentralization premise fails. An L1 dominated by 5-10 entities isn't meaningfully different from a traditional database.
State bloat exceeding solutions. If state growth makes running full nodes impossible for anyone except large institutions, and proposed solutions (state expiry, stateless clients, sharding) fail to materialize or don't work as expected, the L1 becomes effectively centralized in who can verify it.
Migration to superior alternatives. If users and developers abandon an L1 en masse for competing chains that solve the trilemma better, or if Layer 2s become so capable that L1 activity collapses to negligible levels (beyond intended settlement usage), it calls into question whether that L1 remains relevant.
Timing Perspective
Now: Layer 1 blockchains are the foundation of crypto infrastructure. Bitcoin remains the most secure value settlement layer. Ethereum functions as the dominant smart contract platform and L2 settlement layer. Alternative L1s compete on specific tradeoffs (speed vs decentralization, EVM compatibility vs novel architecture).
Next (2026-2027): The L1 vs L2 division becomes more defined. Ethereum's rollup-centric model either succeeds in scaling while maintaining L1 security, or friction and fragmentation push users toward monolithic high-throughput L1s. Client diversity initiatives reach maturity, testing whether redundancy improves or complicates L1 operations.
Later: The question is whether the Layer 1 / Layer 2 distinction persists as the primary categorization, or whether modular architectures blur the lines between consensus, execution, and data availability layers. Long-term viability depends on whether L1s can maintain credible decentralization as they scale—or whether scaling pressures inevitably centralize them.
Boundary Statement
This explanation covers what Layer 1 means as a technical categorization. It doesn't address which specific L1 represents the "best" choice—that depends on use case requirements, risk tolerance, and subjective valuations of speed versus decentralization. The designation "Layer 1" is descriptive, not qualitative.
Whether an L1 is suitable for a given application depends on factors outside this scope: ecosystem maturity, developer tooling, liquidity, and regulatory clarity. Understanding what Layer 1 means helps you evaluate tradeoffs—it doesn't tell you which tradeoffs matter most for your situation.
