An Analysis of Arbitrage Markets Across Ethereum, Solana, Optimism, and Starknet (2024-2025)

Source: Dev.to

Overview

The maturation of public blockchains into global financial layers has fundamentally altered the nature of arbitrage. In the nascent years of DeFi, arbitrage was a game of simple scripts and public mempools—a competitive but largely amateur pursuit.

By 2025, this activity has evolved into a hyper‑specialised, institutional‑grade industry that dictates the economic limits of blockchain scaling. MEV (the total value that can be extracted from block production in excess of the standard block reward and gas fees) has become the dominant economic variable in the design and operation of these networks.

In this article I analyse, from technical and economic perspectives, the arbitrage landscapes on four distinct blockchain architectures:

• Ethereum Layer 1
• Solana
• Optimism
• Starknet

Each network represents a distinct MEV Regime—a unique combination of consensus mechanisms, transaction‑ordering rules, and latency constraints that forces arbitrageurs to adopt radically different strategies.

Key idea: The structure of the underlying chain largely determines the behaviour of the bot.

• Ethereum: separation of proposers and builders turns arbitrage into a sealed‑bid auction for inclusion.
• Solana: lack of a mempool and ultra‑fast block production create a latency‑sensitive streaming auction.
• Optimism: low fees and centralized sequencing incentivise a “spam‑as‑strategy” equilibrium.
• Starknet: zero‑knowledge proof generation times and a developing decentralisation roadmap create a temporary environment of slower, atomic arbitrage.

I have pulled together data and research from late 2024 and 2025 to quantify the number of active bots, their operational costs, and their expected profitability. I also explore the structural shift from “code is law” to “ordering is economy,” where the ability to order transactions is the primary product being sold by validators and sequencers.

The MEV Trilemma in 2025

Arbitrage strategies in the current market cycle are constrained by an MEV Trilemma that forces operators to optimise for two of three variables, often at the expense of the third.

Ethereum Layer 1: The Oligopoly of the Auction House

Ethereum L1 remains the undisputed “heavyweight” arena of global arbitrage. While transaction volumes may be lower than high‑throughput L1s or L2s, the value per transaction and the depth of liquidity create the largest absolute profit pool. The ecosystem has evolved into a rigid hierarchy defined by Proposer‑Builder Separation (PBS), where the “wild west” of priority gas auctions has been replaced by sophisticated supply chains.

The Supply Chain Architecture: Builders, Relays, and Searchers

1. Searchers run algorithms that detect price discrepancies. In 2025 they no longer broadcast transactions to the public mempool; instead they submit bundles—atomic packages of transactions—to builders. A typical bundle contains a user’s transaction followed immediately by the searcher’s back‑run transaction.
2. The searcher attaches a direct payment (the “bribe”) to the builder. If the arbitrage profit is $100, the searcher might bid $90, keeping $10 as net profit. This high bid‑to‑profit ratio defines Ethereum arbitrage.
3. Builders aggregate bundles from thousands of searchers and optimise them to create the most profitable block possible. The market for block building is heavily centralised; by early 2025 the top two builders capture over 90 % of block auctions.
4. Relays are trusted intermediaries that pass block headers from builders to validators, ensuring that validators cannot steal the MEV inside the block.

For an arbitrage bot to be competitive on Ethereum, its primary “skill” is not just identifying opportunities but correctly pricing the bribe. Underbidding leads to exclusion; overbidding erodes profit.

Bot Population and Market Concentration

Empirical analysis of MEV searchers shows that in any given week the number of unique core entities—those consistently winning bids and generating significant profit—rarely exceeds 20. This concentration stems from:

• Capital Requirements: Winning a bundle auction often requires holding substantial inventory of assets to execute trades atomically.
• Infrastructure Costs: RPC fees may run $200–$500 monthly, but the dominant expense is research and development of proprietary pricing models and simulation engines that allow a bot to bid ~99 % of the profit margin without going underwater.
• Long Tail: Hundreds of active addresses attempt arbitrage, but most are peripheral participants capturing sporadic, lower‑value opportunities or employing strategies that do not require fighting for the top‑of‑block position.

Profitability Analysis: The “Black Monday” Case Study

The market turmoil on August 5, 2024 (“Black Monday”) illustrates the scale of profits during volatility:

• Builder 0x3b secured 1,448 ETH in rewards (~$3.5 M).
• Block 20459000 featured a liquidation event that sent 358.7 ETH ($802 k) to the builder.
• An arbitrage bot subsequently paid 36 ETH to the builder for inclusion of its back‑run transaction.

The arbitrage bot likely realized a gross profit far exceeding 36 ETH, but it was forced to pay that amount to the builder to secure inclusion. The builder, in turn, shares a portion with the validator. Data from ESMA and EigenPhi suggest that searchers often pay more than 90 % of their revenue to proposers, leaving a thin margin for the searcher’s net profit.

Strategic Nuances: Sandwiching vs. Atomic Arbitrage

Two primary strategies dominate the Ethereum landscape in 2025:

• Atomic Arbitrage: Simultaneous buying and selling of an asset across different venues (e.g., Uniswap vs. SushiSwap) within a single transaction. This eliminates exposure to market movement but requires precise bundle pricing.
• Sandwiching: Front‑running a victim’s trade by placing a buy order before it and a sell order after, capturing the price impact. This strategy is highly dependent on execution certainty and often yields higher gross profits at the cost of increased competition for block space.

Both approaches hinge on the ability to construct profitable bundles and out‑bid competing searchers within the PBS ecosystem.