Shared L1 AMMs like Uniswap V3 on Ethereum or PancakeSwap on BNB Chain excel at security and composability because they inherit the full consensus security of their underlying chain and exist in a dense ecosystem of DeFi protocols. For example, Ethereum's L1 hosts over $50B in DeFi TVL, enabling seamless integration with lending protocols like Aave and yield strategies via Yearn. This deep liquidity and trustless interoperability are the bedrock for institutional-grade applications.
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Comparisons
Shared L1 AMMs vs Dedicated L2s
A technical comparison for CTOs and protocol architects evaluating the trade-offs between building AMMs on shared Layer 1 blockchains versus dedicated Layer 2 application-specific chains. We analyze performance, cost, security, and ecosystem lock-in.
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introduction
THE ANALYSIS
Introduction: The AMM Scaling Dilemma
A data-driven breakdown of the core architectural trade-offs between deploying an AMM on a shared L1 versus a dedicated L2.
Dedicated L2 AMMs such as dYdX on its custom Cosmos app-chain or Hyperliquid on its own L1 take a different approach by optimizing the entire stack for a single use case. This results in superior performance—dYdX processes over 10 TPS for derivatives with sub-$0.01 fees—but at the trade-off of being a more isolated "silo." While fast and cheap, cross-chain asset transfers and protocol composability require additional bridging infrastructure and introduce new trust assumptions.
The key trade-off: If your priority is maximum security, deep liquidity, and native composability within a mature ecosystem, choose a Shared L1. If you prioritize ultra-low-cost, high-throughput transactions and are willing to manage bridging and a more focused liquidity environment, a Dedicated L2 or App-Chain is the superior choice.
tldr-summary
Shared L1 AMMs vs Dedicated L2s
TL;DR: Key Differentiators at a Glance
A high-level comparison of liquidity deployment strategies. Shared L1 AMMs leverage existing security and composability, while Dedicated L2s optimize for performance and cost.
01
Shared L1 AMMs: Pros
Native Security & Composability: Inherits the full security of Ethereum (~$500B+ secured). Seamlessly composable with major DeFi protocols like Aave, Compound, and MakerDAO.
- This matters for: Protocols where asset safety and deep, cross-protocol integrations are non-negotiable.
02
Shared L1 AMMs: Cons
High Cost & Congestion: Transaction fees are high and variable (often $5-$50+). Throughput is limited by base layer constraints (~15-30 TPS).
- This matters for: High-frequency trading, micro-transactions, or projects targeting mainstream users sensitive to fees.
03
Dedicated L2 AMMs: Pros
Optimized Performance & Cost: Sub-cent transaction fees and high throughput (2,000-4,000+ TPS on zkSync Era, Arbitrum). Enables novel AMM designs like concentrated liquidity (Uniswap V3) at scale.
- This matters for: Applications requiring low-cost, high-speed swaps, perpetuals, and sophisticated order book/AMM hybrids.
04
Dedicated L2 AMMs: Cons
Fragmented Liquidity & Security Assumptions: Liquidity is siloed per chain. Security depends on the L2's specific fraud/validity proofs and bridge design.
- This matters for: Protocols that require the deepest possible liquidity pools or the absolute highest security guarantee of Ethereum settlement.
HEAD-TO-HEAD COMPARISON
Shared L1 AMMs vs Dedicated L2s
Direct comparison of key metrics and features for decentralized exchange infrastructure.
| Metric | Shared L1 AMMs (e.g., Uniswap on Ethereum) | Dedicated L2s (e.g., dYdX, Hyperliquid) |
|---|---|---|
Transaction Cost (Swap) | $5 - $50 | < $0.01 |
Throughput (Orders per Second) | ~20 | 10,000+ |
Settlement Finality | ~15 min (Ethereum L1) | < 1 sec |
Native Order Book Support | ||
Capital Efficiency | Medium (CFMM-based) | High (Order Book-based) |
Protocol Revenue Share | 0.05% - 0.3% fee | Up to 100% via token |
SHARED L1 AMMs vs DEDICATED L2s
Performance & Cost Benchmarks
Direct comparison of key operational metrics for decentralized exchange infrastructure.
| Metric | Shared L1 AMMs (e.g., Uniswap on Ethereum) | Dedicated L2s (e.g., dYdX on StarkEx, Hyperliquid) |
|---|---|---|
Avg. Swap Cost | $5 - $50 | < $0.01 |
Peak TPS (Settled) | ~50 | 10,000+ |
Time to Finality | ~12 min (Ethereum L1) | < 1 sec |
Native MEV Resistance | ||
Protocol Revenue Share | 0.05% - 0.30% | 0.02% - 0.10% |
Settlement Security | Ethereum Consensus | Validity/Plasma Proofs |
pros-cons-a
PROS AND CONS
Shared L1 AMMs vs Dedicated L2s
Key strengths and trade-offs for building or integrating Automated Market Makers (AMMs). Use this matrix to align your protocol's needs with the right infrastructure layer.
01
Shared L1 AMMs: Pros
Maximized Security & Composability: Inherits the full security of the base layer (e.g., Ethereum's ~$100B+ in staked ETH). This enables seamless, trust-minimized composability with major protocols like Uniswap V3, Aave, and Compound. Essential for high-value, cross-protocol DeFi strategies.
Deep, Unified Liquidity: Access to the largest aggregated liquidity pools on-chain (e.g., Ethereum's ~$30B+ DeFi TVL). No fragmented liquidity across rollups. Best for protocols requiring maximum capital efficiency and minimal slippage on large trades.
~$100B+
Base Layer Security
~$30B+
Unified TVL
02
Shared L1 AMMs: Cons
High & Volatile Transaction Costs: User fees are subject to L1 gas auctions (e.g., Ethereum base fees often $5-$50+). This makes small-ticket swaps, micro-transactions, and high-frequency strategies economically unviable.
Throughput & Latency Constraints: Bound by L1 block times and gas limits (~12-15 second finality, ~30 TPS practical limit). Creates poor UX for applications requiring instant feedback, like gaming or high-volume DEX aggregation.
$5-$50+
Typical Swap Cost
~12-15s
Finality Time
03
Dedicated L2 AMMs: Pros
Predictable, Ultra-Low Fees: Native fee abstraction and compressed data on L2s (e.g., Arbitrum, Base, zkSync) enable swaps for <$0.01. Critical for mass-market adoption, micro-transactions, and frequent user interactions.
High Throughput & Customizability: Dedicated blockspace allows for 2,000+ TPS and sub-second pre-confirmations. Chains like dYdX (Orderbook) and Hyperliquid demonstrate L2s can be optimized for specific AMM models (CLOBs, veTokenomics) without L1 constraints.
<$0.01
Swap Fee
2,000+
Potential TPS
04
Dedicated L2 AMMs: Cons
Liquidity Fragmentation & Bridging Friction: Liquidity is siloed on the L2, requiring users to bridge assets (7-day challenge period for some). This creates capital inefficiency and a worse UX compared to native L1 access.
Security Assumptions & Centralization Risks: Security is derived from the L1 but mediated by a sequencer. This introduces liveness assumptions and potential for centralized points of failure (e.g., sequencer downtime), a trade-off unacceptable for some institutional applications.
7-Day
Optimistic Bridge Delay
Sequencer Risk
New Trust Assumption
pros-cons-b
ARCHITECTURE COMPARISON
Shared L1 AMMs vs. Dedicated L2s
Key strengths and trade-offs for liquidity deployment at a glance. Data as of Q2 2024.
01
Shared L1 AMMs: Pros
Immediate Liquidity & Composability: Deploy on Ethereum mainnet (Uniswap V3, Balancer) or Solana (Orca, Raydium) and tap into the chain's native liquidity pool and user base. This matters for protocols that require deep, cross-protocol integration (e.g., lending protocols using AMM LP tokens as collateral).
$4B+
Uniswap V3 TVL
100%
Native Composability
02
Shared L1 AMMs: Cons
High & Volatile Cost Basis: Transaction fees scale with base layer congestion. On Ethereum, a complex swap can cost $50+ during peaks, making small trades and high-frequency strategies (like active LP management) economically unviable. This is a critical constraint for retail users and algorithmic strategies.
$5-$50+
Avg. Swap Cost (Eth)
~15 TPS
Shared Throughput
03
Dedicated L2 AMMs: Pros
Predictable, Ultra-Low Fees: Built on rollups like Arbitrum (Camelot), Optimism (Velodrome), or app-chains like dYdX Chain. Fees are cents or fractions of a cent, enabling micro-transactions, high-frequency arbitrage, and seamless user onboarding. This is essential for consumer-grade dApps and perpetual DEXs.
< $0.01
Avg. Swap Cost
1000+ TPS
Dedicated Capacity
04
Dedicated L2 AMMs: Cons
Fragmented Liquidity & Bootstrapping Cost: You start with an empty order book. Attracting deep liquidity requires significant incentive programs (token emissions, bribes) and battles network effects. Bridges add latency and risk for users. This is a major hurdle for new chains versus established L1 venues.
$10M-$100M+
Typical Incentive Budget
7 Days
Withdrawal Delay (Some Rollups)
CHOOSE YOUR PRIORITY
Decision Framework: When to Choose Which
Shared L1 AMMs for DeFi
Verdict: Choose for deep liquidity and battle-tested security. Strengths:
- High TVL & Network Effects: Protocols like Uniswap, Curve, and Balancer on Ethereum and Arbitrum offer billions in liquidity, reducing slippage for large trades.
- Security & Composability: Inherits the full security of the underlying L1 (e.g., Ethereum). Seamless integration with a vast ecosystem of lending (Aave, Compound), derivatives, and stablecoins.
- Proven Contracts: Audited, forked, and stress-tested over multiple market cycles. Trade-off: Higher gas fees during congestion and slower block times can impact user experience for high-frequency actions.
Dedicated L2s for DeFi
Verdict: Choose for novel, high-frequency, or low-fee applications. Strengths:
- Ultra-Low Fees & High TPS: Chains like zkSync Era, Starknet, and Base offer sub-cent transaction costs, enabling micro-transactions and complex DeFi strategies.
- Customizable Execution: Native account abstraction and custom fee models (e.g., sponsored transactions) improve UX.
- Innovation Sandbox: Faster upgrade cycles allow for novel AMM designs (e.g., dynamic curve AMMs on zkSync). Trade-off: Fragmented liquidity, newer/less audited code, and dependence on L1 for finality and security proofs.
verdict
THE ANALYSIS
Final Verdict and Strategic Recommendation
Choosing between a Shared L1 AMM and a Dedicated L2 is a strategic decision that hinges on your protocol's core requirements for liquidity, control, and user experience.
Shared L1 AMMs (e.g., Uniswap on Ethereum, Orca on Solana) excel at deep, composable liquidity because they are the primary destination for native assets and capital. For example, Uniswap V3 on Ethereum consistently maintains over $3B in TVL, offering unparalleled price stability for major pairs and seamless integration with the broader DeFi ecosystem like lending protocols (Aave) and yield aggregators. This network effect is a powerful moat but comes with the trade-off of higher, variable gas fees and congestion during peak demand.
Dedicated L2 AMMs (e.g., dYdX on StarkEx, Hyperliquid on its own L1, ApeX Pro on zkSync) take a different approach by optimizing for performance and user experience. By operating on a dedicated, application-specific chain or rollup, they can achieve sub-second finality and near-zero trading fees. This results in a trade-off: while they can offer 10,000+ TPS for their core functions, they often sacrifice the deep, permissionless composability of a shared L1, creating a more siloed but highly efficient trading environment tailored for specific use cases like perpetual futures.
The key trade-off: If your priority is maximum capital efficiency, deep liquidity pools, and seamless composability with the broadest DeFi ecosystem, choose a Shared L1 AMM. If you prioritize ultra-low, predictable fees, high transaction throughput, and a tailored trading experience for a specific asset class or product, choose a Dedicated L2. For protocols where user acquisition cost and experience are paramount, the L2's fee savings and speed often outweigh the liquidity fragmentation.
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