Blockspace Under Pressure: An Analysis of Spam MEV on High-Throughput Blockchains

Abstract

On high-throughput, low-fee blockchains, a qualitatively new form of maximal extractable value (MEV) has emerged: searchers submit large volumes of speculative transactions, whose profitability is resolved only at execution time. We refer to this as spam MEV. On major rollups, it can at times consume more than half of block gas, even though only a small fraction of probes ultimately results in a trade. Despite growing awareness of this phenomenon, there is no principled framework for understanding how blockchain design parameters shape its prevalence and impact. We develop such a framework, modeling spam transactions competing for on-chain opportunities under a competitive equilibrium that drives their profits to zero, and deriving equilibrium spam volumes as a function of block capacity, minimum gas price, and the transaction fee mechanism. Empirical evidence from Base and Arbitrum supports the model: spam grew sharply as block capacity was scaled up and fell when minimum gas prices were introduced. Our analysis yields three main insights. First, spam is always costly: when block capacity is scarce, it displaces users and drives up gas prices; as block capacity grows, it increasingly consumes execution resources, raising network externality, i.e., the cost of provisioning and processing blocks. We show that spam takes an increasing share of each additional unit of block capacity, so capping it before all users are included creates a favorable trade-off: forgoing a small amount of user welfare eliminates disproportionate spam and externality. Second, we extend the analysis to priority fee ordering and show that ordering transactions by gas price helps reduce spam, as spammers must pay more to reach early block positions. Third, as user demand grows and blockspace is scaled accordingly, spam's share of block capacity plateaus rather than growing indefinitely.

Figures (16)

• Figure 1: Spam and non-spam gas on Base over time (7-day moving averages). The right axes show the gas target.
• Figure 2: Daily spam gas on Base and Arbitrum (7-day moving averages). The right axes show the median fee and protocol minimum gas price (log scale).
• Figure 3: Linear demand curve $D(g) = D_0 - \beta g$. At clearing price $g^*$, the shaded triangle is the user welfare (aggregate surplus of included users).
• Figure 4: Equilibrium spam volume as a function of block size $B_\text{max}$, and the gas share of spam transactions out of total included gas. Spam is $0$ when the block is small and the clearing price is high. As $B_\text{max}$ grows, entry becomes more profitable and spam begins to rise. Once $B_\text{max}$ reaches $B_{\mathrm{plat}}$, the gas price is pinned at $g_\text{min}$ and spam plateaus. In this figure, $D_0=1200$, $\beta=6$, $s=20$, $r_0=6000$, and $g_\text{min}=20$.
• Figure 5: Levels of user welfare, validator revenue, and externality, with and without spam, as functions of block size. Each panel compares the spam world to the spam-free counterfactual at the same $(B_\text{max},g_\text{min})$.

Theorems & Definitions (12)

• Definition 2.1: User Welfare
• Definition 2.2: Validator Revenue
• Definition 2.3: Network Externality
• Remark 3.1: Connection to Mazorra et al.
• Proposition 3.2: Welfare Loss Peaks at $D(g_\text{min})$
• Proposition 3.3
• Remark 7.1: A note on spam volume with PFO and random ordering.
• Proposition A.1
• proof
• Remark C.1