L1 Builder/Auction Settings in Blockchain

• L1 Builder/Auction Settings are mechanisms in blockchain that define auction formats, reserve pricing, and workflows to allocate block construction rights.
• They implement lazy and eager reserve strategies, balancing revenue, welfare, and market centralization in environments like Ethereum's Proposer-Builder Separation.
• Practical heuristics, such as reserve tuning, A/B testing, and transparency measures, help manage strategic bidding, order flow diversity, and system fairness.

Layer-1 (L1) builder/auction settings designate the mechanisms, parameters, and workflows by which block construction rights and transaction orderings are allocated in blockchain systems, particularly those such as Ethereum operating under Proposer-Builder Separation (PBS). These settings regulate the auction market that mediates between proposers (validators), builders (block producers), and, by extension, searchers (order flow providers), controlling both the economic incentives and the levels of decentralization attainable in the system.

1. Mechanism Definitions: Auction Formats and Reserve Pricing

L1 builder/auction settings encapsulate the precise auction format and the rules for personalized reserve prices, which are fundamental for determining allocation, pricing, and revenue guarantees. Two canonical second-price auction variants are widely implemented in PBS-driven environments (Leme et al., 2016):

(a) Lazy (2SP-Lazy) Reserve Pricing:

• Allocation: Winner determined as $i^* = \arg\max_i b_i$; sale only if $b_{i^*} \geq r_{i^*}$.
• Payment: $p_{i^*} = \max\{ r_{i^*}, b^{(2)} \}$ (second price or reserve).
• Optimization: Computable in $O(T \log T)$ from logs by isolating each bidder’s win/loss and deriving the maximizing reserve.

(b) Eager (2SP-Eager) Reserve Pricing:

• Allocation: Discard bidders with $b_i < r_i$, then allocate to highest among survivors.
• Payment: $$p_{j^*} = \max\{ r_{j^*}, \max_{i \in S \setminus \{j^*\}} b_i \}$$.
• Optimization: NP-hard due to dependency on which combinations of bidders surpass reserves; only admits approximation via lazy-reserve initialization.

Revenue and Welfare Properties:

• Eager reserves yield higher welfare ($\text{Welfare}_E \geq \text{Welfare}_L$).
• Revenue between optimal lazy and eager settings is within a factor of $2$.
• Under symmetric or independent bidding, eager reserves achieve at least as much revenue as lazy reserves.

Practical Heuristics:

• Use coordinate descent with convex-like relaxations or initialize eager reserve optimization with lazy-optimal reserves for 2-approximation.
• Compute monopoly reserves (simple one-dimensional maximization) as a warm start.

2. Layer-1 PBS Auction Workflows: MEV-Boost and Protocol Enshrinement

MEV-Boost-Style (Off-Chain) Workflow (Koegler, 22 Jun 2025, Yang et al., 2024):

• Roles: Proposers (validators) outsource block construction to off-chain builders via relays.
• Every slot: Builders prepare a bid $b_i$ and a sealed payload header. Relays aggregate, propose to the validator, and upon signature, deliver the block.
• Mechanism: Sealed first-price auction—highest bidder wins, pays their bid.

Enshrined PBS (ePBS, EIP-7732) (Wang et al., 19 Jan 2026, Koegler, 22 Jun 2025):

• On-chain auction, 24 mini-round (first-price, commit-reveal) within each slot. Bids are sealed and only revealed post-commitment.
• Auction winner: $b_{i,T} = \max_n b_{n,T}$; proposer collects full or near-full bid as revenue.
• Enshrined enforcement of relay commitment, slashing, and reveal deadlines.

Communication and Settlement:

• Bid commitment and payload header submitted as on-chain (or off-chain relay) messages.
• Proposer includes selected builder’s payload in the canonical chain; on-time reveal enforced with fork-choice weight penalties or rewards.

Fee Accounting:

Component	Formula	Recipient
Proposer	$b_{i^*} \geq r_{i^*}$0	PoS withdrawal addr.
Builder	$b_{i^*} \geq r_{i^*}$1	Builder stake addr.
Base fees	EIP-1559 burned	N/A

• $b_{i^*} \geq r_{i^*}$2 = protocol-sponsored rewards; $b_{i^*} \geq r_{i^*}$3 = builder auction clearing price.

3. Auction Dynamics: Strategic Bidding, Centralization, and Market Structure

Information Access and Asymmetry (Wang et al., 2024, Wu et al., 2023, Öz et al., 2024):

• Exclusive private order flow access is the primary determinant of builder market share, profit margin, and win rate.
• Asymmetric information induces bid shading: strong (high-private-flow) builders shade bids more, yet win more slots and accrue disproportionate profits.

Bidder Strategies:

• Adaptive, last-minute, and bluff bidding emerge under latency heterogeneity and continuous first-price auction mechanics (Wu et al., 2023).
• Lower relay/network latency yields measurable win-rate and profit increases; exclusive order flow access delivers even larger gains.
• Strategic shading in first-price settings increases with concentration and asymmetric information.

Empirical Centralization Outcomes (Wang et al., 2024, Wang et al., 19 Jan 2026, Yang et al., 2024):

• Top 2–3 builders hold >85–90% of block production, with builder-profit Gini coefficient often exceeding 0.8 under ePBS.
• Feedback loop: More private order flow → more wins → more exclusive flow → increased dominance.
• Proposer share remains decentralized due to random slot assignment and martingale stake evolution (Ma et al., 17 Feb 2025).

4. Impact of Order Flow Diversity and Exclusive Access

Builder competitive edge is rigorously characterized by four major features (Öz et al., 2024):

Feature	Measurement (for builder B)	Correlation with Share/Profit
Order-flow diversity	Shannon entropy $b_{i^*} \geq r_{i^*}$4 across 12 categories	$b_{i^*} \geq r_{i^*}$5 0.66
Exclusive-signal	Value share in non-mempool txns/OFA bundles	$b_{i^*} \geq r_{i^*}$6 0.7
Non-atomic arbitrages	Value share from CEX–DEX, private, unlabelled trades	$b_{i^*} \geq r_{i^*}$7 0.6
Telegram-bot flow	Value share from known bots’ trades	$b_{i^*} \geq r_{i^*}$8 0.6–0.7

• Concentration in any of these features entrenches entry barriers and weakens censorship resistance.
• “Chicken-and-egg”: builders need private flow to profit, but only receive it with high market share.
• Protocols should enforce public order-flow equality, design sealed-bid auctions, and monitor builder dominance.

5. Role Selection, Incentive Alignment, and Auction Composition

Two-Sided Market Dynamics (Li et al., 19 Mar 2025):

• Searchers (bundle providers) decide between acting as builders or sharing bundles, influenced by conflict probabilities.
• Equilibrium shifts from searcher- to builder-dominated as bundle-conflict probability $b_{i^*} \geq r_{i^*}$9 exceeds a threshold ($p_{i^*} = \max\{ r_{i^*}, b^{(2)} \}$0).
• Builder rebates, searcher payoffs, and proposer revenue are all non-monotonic and depend on conflict/competition structure.

Order-Flow Auction (OFA) (Ma et al., 17 Feb 2025):

• Order flow is sold to builders who then bid in the block-building auction.
• Nash equilibrium: competitive advantage compounds as stronger builders pay (and bid) less relative to their MEV edge, driving centralization.
• Validator shares evolve as martingales—proposer decentralization is robust.

6. Practical Heuristics, A/B Testing, and Design Recommendations

Reserve Price Tuning (Leme et al., 2016):

• Lazy reserves: Optimal always computable efficiently from logs.
• Eager reserves: Intractable, but 2-approximation via lazy-opt reserves is effective.
• A/B testing: Use auction-level or cluster randomization; avoid partial assignment for eager reserves, as partial treatment can paradoxically reduce revenue.

Parameterization and Enforcement (Koegler, 22 Jun 2025, Wang et al., 2024):

• Ensure open access to order flow and transparency in bid submissions.
• Implement minimum builder stakes, slashing for non-reveal, and enforce deadlines to deter misbehavior.
• Design inclusion-list or fair-share quotas to guard against censorship and builder monopoly.

Best Practice	Mechanism or Parameter
Auction-level randomization	Assign entire auctions to control or treatment groups
Minimum overbid increment	Granular bid steps to dampen penny-stealing
Information symmetry	Public sharing of exclusive bundles, or thresholded
Slashing & enforcement	Penalties for failed payload reveals

Experimental Best Practices:

• Compute optimal lazy reserve, apply eagerly, and fine-tune via local ascent.
• Use moving-average target revenue for future-block reservation auctions.
• Monitor HHI/Gini metrics and adapt entry/bid policies accordingly.

7. Open Questions and Forward Directions

Consensus is converging on several protocol-level issues and design questions:

• Does future-block reservation (e.g., Flashback) meaningfully shift fee split or builder/proposer equilibria? (Mao et al., 2024)
• How should mechanisms optimally enforce openness of order flow without unduly reducing MEV extraction?
• What is the welfare-maximizing split between proposer rewards, builder incentives, and user rebates under endogenous entry and strategic shading?
• How can protocols detect and correct builder collusion or censorship in a trust-minimized way?
• Are hybrid or multi-winner auctions viable given empirical flow and latency characteristics?

Empirical work and agent-based simulations continue to quantify the trade-off space, with increasing focus on economic security, fairness, and composability between auction layers.

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Key Citations: (Leme et al., 2016, Wu et al., 2023, Yang et al., 2024, Mao et al., 2024, Wang et al., 2024, Ma et al., 17 Feb 2025, Li et al., 19 Mar 2025, Koegler, 22 Jun 2025, Wang et al., 19 Jan 2026, Öz et al., 2024)