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Ethereum vs Modular L1s: Gas Costs

A technical analysis comparing the gas cost structures of monolithic Ethereum and modular L1s like Celestia, Avail, and EigenDA. We break down fee drivers, predictability, and architectural trade-offs for infrastructure decisions.
Chainscore © 2026
introduction
THE ANALYSIS

Introduction: The Core Cost Dilemma

A data-driven breakdown of the fundamental trade-offs in transaction cost models between Ethereum and its modular L1 competitors.

Ethereum excels at providing unparalleled security and decentralization, which results in a premium, market-driven gas fee. Its monolithic architecture processes all transactions, smart contract execution, and data availability on a single layer, leading to high demand and volatile costs. For example, during peak NFT minting or DeFi activity, average transaction fees can surge above $50, making simple swaps prohibitively expensive. However, this cost secures your application on a network with over $50B in Total Value Locked (TVL) and the most robust validator set in crypto.

Modular L1s like Solana, Avalanche, and Near take a different approach by specializing layers for specific functions (execution, consensus, data) and optimizing for raw throughput. This architectural strategy results in significantly lower and more predictable fees—often fractions of a cent—but involves trade-offs in decentralization or requires trust in more centralized data availability layers. Solana, for instance, achieves ~3,000-5,000 TPS with sub-$0.001 fees, but has faced network instability, highlighting the performance-reliability balance.

The key trade-off: If your priority is maximum security, deep liquidity, and ecosystem maturity for a high-value DeFi or institutional application, Ethereum's cost is a justifiable premium. Choose a Modular L1 or an Ethereum L2 like Arbitrum or Optimism when your priority is low-cost, high-frequency transactions for consumer dApps, gaming, or micro-payments, and you can accept a different security model or a younger ecosystem.

tldr-summary
Ethereum vs Modular L1s: Gas Costs

TL;DR: Key Differentiators at a Glance

A direct comparison of gas cost structures, predictability, and long-term scaling trajectories.

01

Ethereum: Predictable & Universal Pricing

Single, global gas market: All execution, data, and state compete on one price curve (EIP-1559). This creates predictable, uniform costs for all applications, which is critical for DeFi protocols like Uniswap and Aave that require stable operational budgeting.

02

Ethereum: High Security Premium

Gas fees fund the world's largest crypto-economic security budget (~$30B+ staked). You pay for the gold-standard of decentralization and censorship resistance. This is non-negotiable for high-value, trust-minimized applications like Lido or MakerDAO.

03

Modular L1s: Radically Lower Absolute Cost

Specialized execution layers (e.g., Celestia + Rollups, EigenLayer AVS) decouple execution from consensus/data availability. This enables sub-cent transaction fees, making them viable for high-frequency micro-transactions in gaming (e.g., Paima Studios) or social apps.

04

Modular L1s: Variable & Complex Cost Structure

Fragmented fee markets: Costs depend on separate execution, data availability (DA), and settlement layers. DA costs (e.g., on Celestia or EigenDA) can spike independently, creating unpredictable budgeting for dApps. Requires active management across multiple layers.

ETHEREUM VS MODULAR L1S

Feature Matrix: Gas Cost & Structure Head-to-Head

Direct comparison of transaction economics and architectural trade-offs.

MetricEthereum (Monolithic L1)Modular L1 (e.g., Celestia)

Avg. Transaction Cost (Base Layer)

$1.50 - $50+

< $0.01

Fee Structure

Dynamic Auction (First-Price)

Fixed/Deterministic

Gas Token

ETH (Native)

Native Token or ETH via Bridging

State Growth Cost

High (Full Nodes)

Minimal (Data Availability)

Fee Predictability

Low (High Volatility)

High (Stable, Pre-set)

Throughput (Data Layer)

~80 KB/s

~8 MB/s+

Settlement Finality

~15 minutes

~10-20 seconds

ETHEREUM L1 VS. MODULAR L1S (AVALANCHE, SOLANA)

Cost Analysis: Transaction Fee Benchmarks & Predictability

Direct comparison of transaction cost structures and predictability for infrastructure decisions.

MetricEthereum (L1)Modular L1s (e.g., Avalanche, Solana)

Avg. Simple Transfer Cost (USD)

$1.50 - $5.00

$0.001 - $0.10

Avg. DEX Swap Cost (USD)

$5.00 - $20.00

$0.01 - $0.25

Fee Predictability

Low (High Volatility)

High (Stable, Low Volatility)

Base Fee Mechanism

EIP-1559 (Auction + Burn)

Fixed Fee or Minimal Auction

Priority Fee (Tip) Required

Max Theoretical TPS

~30

4,500+ (Avalanche), 65,000+ (Solana)

Fee Reduction via L2

true (Arbitrum, Optimism)

null

pros-cons-a
PROS & CONS

Ethereum (Monolithic) vs Modular L1s: Gas Costs

A direct comparison of gas cost structures for monolithic execution versus modular data availability and settlement layers.

01

Ethereum: Predictable Fee Market

Specific advantage: Gas fees are determined by a single, transparent auction (EIP-1559) on the base layer. This provides cost predictability for protocols like Uniswap and Aave that require stable operating economics.

This matters for DeFi applications where user experience and profit margins depend on forecasting transaction costs, not competing with unrelated data blobs.

02

Ethereum: Security Premium

Specific advantage: Fees pay for the gold-standard security of the Ethereum Virtual Machine (EVM) and its ~$110B+ staked economic security. Every transaction is validated by the same decentralized validator set that secures the entire state.

This matters for high-value settlements, institutional DeFi, and protocols where the cost of a security failure far outweighs gas expenses.

03

Modular L1s (e.g., Celestia): Minimal Base Cost

Specific advantage: By offloading execution to rollups, the base layer (DA) charges for data publishing only. Costs are driven by blob space, not computation, leading to fees often 100-1000x cheaper for raw data (e.g., ~$0.01 per 125 KB blob).

This matters for scaling social apps, gaming, and high-throughput dApps where cost-per-interaction must be negligible.

04

Modular L1s: Variable Rollup Pricing

Specific disadvantage: End-user gas costs are set by individual rollups (e.g., Arbitrum, zkSync) and their sequencers. This creates a fragmented fee market where costs can spike on one rollup while others remain cheap, adding complexity for multi-chain dApps.

This matters for developers managing cross-rollup liquidity or users who need consistent costs across different applications.

pros-cons-b
PROS & CONS

Ethereum vs Modular L1s: Gas Costs

Key strengths and trade-offs for gas costs at a glance.

01

Ethereum: Predictable & Secure Pricing

High but stable base fee: Gas costs are determined by a robust, auction-based EIP-1559 mechanism, providing predictable fee estimation for users and dApps like Uniswap and Aave. This matters for enterprise applications requiring budget certainty and high-value transactions where security is paramount.

02

Ethereum: High On-Chain Execution Costs

Expensive computation: Mainnet gas fees for complex operations (e.g., NFT minting, DeFi swaps) can exceed $50+ during congestion. This is prohibitive for high-frequency micro-transactions and mass-market consumer dApps, pushing volume to L2s like Arbitrum and Optimism.

03

Modular L1s: Ultra-Low Data Availability

Sub-cent data posting: Protocols like Celestia and Avail decouple data availability (DA), offering blob space for ~$0.003 per MB. This matters for high-throughput rollups (e.g., Eclipse, Fuel) and sovereign chains needing to minimize their largest operational cost.

04

Modular L1s: Execution Cost Uncertainty

Variable settlement & proving fees: While DA is cheap, users still pay for execution on connected rollups and proving on networks like EigenDA. Total cost depends on the modular stack's maturity and can be opaque compared to Ethereum's unified fee market. This matters for developers evaluating total cost of ownership.

CHOOSE YOUR PRIORITY

Decision Framework: Choose Based on Your Use Case

Ethereum for DeFi

Verdict: The Unquestioned Liquidity Hub. Strengths: Dominant TVL (>$50B), battle-tested smart contracts (OpenZeppelin), and the deepest liquidity pools (Uniswap, Aave, Compound). Security and composability are paramount. Weaknesses: High and volatile gas fees can cripple user experience for small trades and complex interactions.

Modular L1s (e.g., Arbitrum, Base, zkSync) for DeFi

Verdict: The Scalable Execution Layer. Strengths: Drastically lower fees (often <$0.01) enable micro-transactions and complex DeFi strategies. Faster block times improve UX. Inherits Ethereum's security via rollup proofs or validation. Weaknesses: Liquidity is fragmented; bridging introduces latency and risk. Protocol dominance is still consolidating.

Decision: Build on Ethereum L1 for maximal security and liquidity if your protocol handles large, infrequent value transfers. Use a leading Modular L2 for any high-frequency, user-facing dApp where cost and speed are critical.

verdict
THE ANALYSIS

Verdict: Strategic Cost Considerations

A data-driven breakdown of gas cost models, revealing the fundamental trade-off between predictable fees and variable throughput.

Ethereum excels at providing a stable, predictable, and secure cost environment for high-value transactions. Its high base-layer security and mature ecosystem, with over $50B in TVL, justify its premium gas fees. For example, a complex DEX swap or NFT mint on mainnet can cost $10-$50, but this cost is a known variable for budgeting, and tools like EIP-1559 provide fee predictability. This model is optimal for applications where finality and security are non-negotiable, such as institutional DeFi or high-value asset settlement.

Modular L1s (e.g., Celestia, Avail) take a different approach by decoupling execution from consensus and data availability. This specialization drives down costs by orders of magnitude. A similar swap on a rollup using Celestia for data can cost less than $0.01. The trade-off is a more fragmented security model and reliance on bridging. You gain massive scalability and low fees but must manage dependencies on separate data availability layers and potentially less battle-tested consensus mechanisms.

The key trade-off: If your priority is maximum security, deep liquidity, and a unified settlement layer for billion-dollar TVL applications, choose Ethereum and its L2 ecosystem (Arbitrum, Optimism). If you prioritize ultra-low, predictable transaction costs (sub-cent) and are building a high-throughput application like a social media dApp or a hyper-casual game, a modular L1 stack provides the necessary economic scalability.

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