EVM Workloads in the Wild: Evidence for Multi-Dimensional Gas Metering, State Growth, Delayed Execution, and Parallelism

2026-06-18

AI Summary

This study addresses the limitations of Ethereum’s current single-dimensional gas model, which overlooks resource heterogeneity and state dependency, leading to unpredictable transaction fees. By conducting the first large-scale empirical analysis of 3,000 daily blocks from both Ethereum L1 and Base L2 in 2025, the work combines opcode-level gas decomposition, historical state re-execution, and storage access pattern tracing to quantify the dynamic consumption of multidimensional resources—such as computation and storage—and sensitivity to state changes across transactions. The findings reveal that Base’s state size (456 GB) vastly exceeds Ethereum’s (38 GB), 46% of transactions exhibit significant gas variability with state evolution, and cold reads are prevalent with unstable access patterns. These insights provide critical empirical support for multidimensional gas pricing, explicit state-growth charging, and optimizations for parallel execution.

Abstract

Gas metering on EVM-compatible blockchains assumes that execution conditions are stable: that the resource mix is constant enough to justify collapsing execution costs into a single scalar with fixed relative prices, and that state drift between submission and execution does not materially alter a transaction's outcome. We measure the extent to which this assumption fails. We present a trace-level measurement study of EVM workloads on Ethereum (L1) and Base (L2) throughout 2025, sampling 3,000 blocks per day per chain. We decompose each transaction into opcode-level execution gas, intrinsic gas, refunds, and persistent state deltas. To measure state sensitivity, we re-execute transactions from September 2025 on older states and record how gas usage and storage access patterns change. We find the resource mix to be far from stable: on Base, storage reads and compute account for 29.2% and 24.3% of execution gas, while Ethereum devotes 34.9% to storage writes. Ethereum's gas limit doubling during 2025 shifted its own profile toward compute-heavier, Base-like patterns. Base also exhibits a higher fraction of cold storage reads (49.7% versus 39.6% on Ethereum). Persistent state growth, a permanent cost priced as a transient one, reaches 456 GB on Base versus 38 GB on Ethereum. Execution outcomes are equally unstable: gas estimates vary across nearby historical states for 46.0% of transactions on Base, compared to 13.9% on Ethereum, with especially high sensitivity for MEV and DeFi activity. Storage access patterns also diverge across states, limiting the effectiveness of access lists and complicating parallel execution. Our work provides an empirical foundation for multi-dimensional gas metering and explicit pricing of state growth. They show that state-sensitive execution behavior complicates workload estimation, directly affecting transaction predictability and user experience.

Problem

• EVM
• gas metering
• state sensitivity
• workload variability
• transaction predictability

Innovation

• multi-dimensional gas metering
• state sensitivity
• EVM workloads
• state growth pricing
• transaction re-execution