Why the EVM's Design Dooms It to Centralization

Synchronous execution is a bottleneck. Every transaction must be processed sequentially by a single node, creating a hard limit on throughput that only expensive hardware can overcome. This creates a validator oligopoly where only well-funded entities can run performant nodes, centralizing the network's core infrastructure.

State bloat guarantees centralization. The requirement for every node to store the entire chain's history creates an insurmountable data burden. Solutions like Erigon's flat storage model or Ethereum's Verkle trees are patches, not fixes; they delay but do not prevent the inevitable centralization of archival nodes.

L2s export, not solve, the problem. Rollups like Arbitrum and Optimism inherit the EVM's execution model. Their sequencers are centralized points of failure today, and their long-term decentralization roadmaps depend on unproven, complex mechanisms like shared sequencer networks that reintroduce consensus overhead.

Evidence: Node Counts Tell the Story. Ethereum has ~9,000 consensus nodes, but only three clients (Geth, Erigon, Nethermind) dominate execution. For L2s, the active validator set is often a single entity. This is the logical endpoint of an architecture that prioritizes a single, globally-shared state over parallel, sovereign execution.

Single-threaded execution is the EVM's fundamental flaw. Transaction processing is a sequential queue, not a parallel workflow. This creates a deterministic performance ceiling where the fastest single CPU wins, forcing validators into a hardware arms race.

Monolithic global state compounds the problem. Every node must store and compute against the entire world state. This creates massive hardware requirements, making solo staking economically unviable and pushing users toward centralized providers like Lido and Coinbase.

The hardware race centralizes block production. High-performance nodes from Blockdaemon or Chorus One outcompete commodity hardware. The network's security model shifts from decentralized consensus to trust in a few optimized operators, mirroring the pitfalls of Solana's validator requirements.

Evidence: Ethereum's Nakamoto Coefficient for consensus is estimated at 2-3 entities. Over 60% of consensus-layer clients run on minority software, creating systemic risk from a single bug. This is a direct consequence of the execution bottleneck.

Sequencer Centralization is Inevitable. The EVM's synchronous execution model demands a single, authoritative state ordering machine. This creates a natural monopoly for the sequencer role, as seen with Arbitrum and Optimism's centralized operators. Decentralized sequencer sets like Espresso or Astria remain theoretical and add latency, defeating the L2 performance promise.

Proposer-Builder Separation Fails Here. Unlike Ethereum's PBS which separates block building from proposing, L2 sequencers consolidate both functions. This creates a single-point-of-failure for censorship and MEV extraction, a problem protocols like Flashbots' SUAVE aim to solve on L1 but are architecturally blocked on monolithic rollups.

The Data Availability Crutch. Validiums and so-called 'L3s' (e.g., StarkEx apps) offload data to centralized Data Availability Committees or alternative layers like Celestia/EigenDA. This trades Ethereum's security for scalability, creating a fragmented security landscape where users must trust new, unproven networks.

Evidence: Over 95% of Arbitrum and Optimism transactions are ordered by their respective centralized sequencers. The economic incentive to capture sequencer MEV, estimated in billions annually, guarantees this centralization persists.