Alt-L1 Validators vs. Ethereum L2 Data Availability: Cost Comparison for Chain Operators
In this blog, we compare onchain costs for L1s (validator payouts) versus L2s (data availability and ZK proving).
If you’re launching a new chain, one of the most important decisions you’ll make is whether to build an L1 or an L2 on Ethereum. The alt-L1 vs. Ethereum L2 decision has several components, including growth potential, time to market, and customizability.
But one of the most important factors is cost. And the biggest onchain costs are driven by how you secure the chain. For alt-L1s, that means validator incentives. For L2s, it means data availability, and potentially ZK proving costs. Let's examine the differences in onchain costs between alt-L1s and Ethereum L2s.
Run the numbers yourself with our L1 vs. L2 cost comparison calculator!
Onchain costs: Validators and data availability explained
All blockchains need to do two things in order to function securely:
- Only accept and finalize valid transactions – no double spend or broken rules.
- Ensure the network agrees on a single ordered history of transactions so that balances and app state are reliable.
If either fails, users can’t trust that their assets are safe. It’s important that no single trusted party has total control of these functions, as they could then censor transactions or push through invalid transactions. The biggest difference between alt-L1s and Ethereum L2s – and one that greatly influences costs for chain operators – is in the security models they use to fulfill these functions.
L1s rely on validator sets running proof-of-stake consensus. Validators take turns proposing blocks while others attest. Once quorum rules are met, blocks become canonical and reach finality. Chains compensate validators for this in the chain’s native token via issuance and the sharing of transaction fees – sometimes one or the other, sometimes a combination of both. Likewise, validators stand to lose money via slashing if they propose invalid transactions
Ethereum L2s inherit settlement security from Ethereum mainnet, allowing them to optimize for throughput and UX. Their primary security cost is data availability (DA). The L2’s sequencer node orders transactions much faster than a distributed validator set can, but then publishes the data to Ethereum so that anyone can reconstruct and audit those transactions – the L2s pay fees to Ethereum based on how much data they post. L2s enforce transaction validity through their proving model – optimistic rollups allow users to challenge transactions during a set window via fraud proofs, while ZK rollups use validity proofs, which are faster and better for interoperability, but add significant costs. If the sequencer misbehaves or censors, users can also withdraw their funds via smart contracts on Ethereum mainnet.
Cost comparison: Alt-L1s vs. Ethereum L2s
In summary, alt-L1s’ primary onchain costs come from:
- Token issuance to validators
- Share of transaction fees and MEV to validators
Ethereum L2s’ primary onchain costs come from:
- DA costs per byte of transaction data posted
- ZK proving costs per transaction batch (one batch requires one validity proof)
Cost calculator
You can try running the numbers yourself on our L1 vs. L2 cost calculator:
Let’s dive into what drives the numbers below.
Alt-L1 validator costs
Alt-L1s pay validators via new token issuance and transaction fee sharing, or a combination of both. Chains choose the exact model for themselves based on tokenomics and their strategy for incentivizing validators. BNB Chain, for instance, issues no new tokens and pays validators 90% of all transaction fees generated, burning the rest – a model geared towards deflationary tokenomics. Solana, on the other hand, pays validators through a combination of token issuance and fee sharing. On the issuance side, the chain began with an initial target new token issuance rate of 7-9%, and is gradually lowering that to a target of 1.5% – as of September 2025, new token issuance is at 5%. Validators receive those new tokens, plus a share of transaction fees.
Overall, the cost of validator rewards varies greatly depending on the chain and the value of its token.
The formula for validator costs is:
Validator_costs = (tokens_issued * token_price) + (total_fees * validator_fee_share_percentage * token_price)
Here’s what a few notable L1s have paid out to validators in the 30 days up through September 9, 2025. [1]
Validator payout amounts range widely because of high variance in the formulas for how different L1s determine payments, and because payout amounts are so dependent on token price. As we’ll see in the next section though, validator payout costs are generally much larger than the onchain security costs for L2s, though ZK proving can push L2 costs closer.
However, those costs are worth it for many projects. The validator staking model gives L1 tokens clearer utility – that, combined with a historic investor premium for L1s, can lead to higher token prices. L1 validator sets are also generally perceived as more credibly neutral than the single sequencer setup of L2s, which can make the L1 model a better option for projects targeting institutional users and traditional financial institutions, who tend to prioritize neutrality of shared infrastructure.
Ethereum L2 data availability and ZK proving costs
Data availability costs
Whereas validator costs range widely for alt-L1s depending on payout model and token price, DA costs are more standardized. L2s pay based on the amount of data they settle, and fees fluctuate with demand – the more data other chains are trying to post at any given time, the higher the fee.
The formula for DA costs is:
DA_cost = (transaction_data_MB_posted * DA_price_per_MB)
The price per MB fluctuates with demand, and also varies by DA provider. The default is to use Ethereum’s native blobs mechanism, but you can also use alt-DA providers like Celestia and EigenDA, which are generally cheaper – our previous research suggests that Celestia is up to 25x cheaper than Ethereum blobs. However, both solutions have seen lower prices since then.
Below, we’ll look at DA costs for a few notable Ethereum L2s using both blobs and Celestia over the 30-day period ending on September 9, 2025. [2]
Overall, DA costs for L2s are much lower and more predictable than validator costs for L1s. Celo provides the most direct possible comparison, as it transitioned from an L1 to an L2 – in the last month before that transition, its validator payout costs were $641,540 versus just $1,070 in DA costs for the last 30 days.
Those lower and more predictable costs, along with greater customizability, make Ethereum L2s better-suited for appchains built around one specific use case, and projects prioritizing profit and loss along with token price. However, the range of use cases and constant innovation in the space means this can change over time and depending on the specific project.
ZK proving adds significant costs to the rollup model, but not without major benefits – and costs are trending down
As mentioned previously, a ZK proof system would add significant further costs. Succinct Labs estimates that its OP-Succinct ZK proving system adds a cost of roughly $0.005 per transaction. [3]
ZK_cost = $0.005 * (number_of_transactions)
In order to compare ZK costs with DA costs, we'll assume an average data load of 150 bytes per transaction. That works out to roughly $33.33 per MB of data settled. This would dwarf DA costs for most chains. Take Base, for example: ZK proving would push its per-MB costs from $2.64 to $35.97, and lift its total onchain costs for the time period studied from $128,650 to $1.75 million. While this is still a lot less than what a comparably sized alt-L1 would pay out to validators, it’s a large increase.
Many L2s would say those costs are worth it though. ZK proving enables fast withdrawals – while optimistic rollups must delay user withdrawals by seven days to account for the fraud proof dispute window, ZK rollups can allow users to withdraw in 15 minutes to one hour. That greatly improves UX, and allows chains to address institutional users who simply can’t afford for funds to be tied up for so long. Fast withdrawals also improve interoperability with other chains.
It’s also worth noting that ZK proving costs don’t scale linearly – the more transactions you’re proving, the lower proving costs go on a per-transaction basis. ZK proving costs are also trending downward generally, and providers like Succinct and Boundless offer ZK fraud proofs, which function as a hybrid of the optimistic and ZK model, in which ZK proofs are used only to settle disputes rather than continuously prove all transactions. That reduces costs significantly.
Don’t forget offchain costs
Beyond the onchain costs outlined above, you also need to consider the offchain costs of running your chain:
- Validator recruitment: New L1s typically run early grant, delegation, and airdrop programs to bootstrap new validator sets.
- Ecosystem and liquidity incentives: Both L1s and L2s offer incentives for apps, liquidity providers like market makers, and other key integrations. These costs are generally higher for alt-L1s, as they must recruit a greater range of partners and seed more depth across more tokens, and there’s no native connectivity to a bigger chain like L2s have with Ethereum. Within the world of L2s, appchains focused on a single use case will have lower costs than a general purpose chain.
- Infra and operations: Budget for RPCs, block explorers, indexers, data analytics, alerting, backups, incident response, and wallets. Alt-L1s have added coordination and monitoring overhead given their distributed validator set, while L2s must account for DA monitoring and sequencer failover. On net, these costs are generally slightly lower on L2s.
- Engineering costs: Alt-L1s own the full stack (consensus, networking, mempool, fork-choice, light clients), making ongoing engineering higher-cost in general. L2s inherit much of that work from their rollup frameworks (OP Stack, Arbitrum Orbit, etc.) and focus on rollup node, batcher, bridge, and framework upgrades – usually lower-cost unless the chain is heavily customized.
In general, these costs tend to be higher for alt-L1s.
L1s are more expensive to run, but offer unique benefits your project may need
Onchain costs are significantly higher for L1s than for L2s. This raises the question: Why launch an L1?
As discussed above, there are two primary reasons. The first has to do with credible neutrality. Many believe that a decentralized validator set is necessary for certain use cases, especially those targeting existing financial institutions and associated functionalities like payments or bank deposit tokenization. The basic argument would be that those users don’t want to risk any potential for transaction censorship or unexpected changes to the chain. While single-sequencer L2s have mechanisms in place to mitigate those risks, and many are exploring sequencer decentralization, some would argue that an L1 with a decentralized validator set removes all doubt of misalignment between chain operator and user. Whether this perception persists long-term remains to be seen – we’re still in the early innings.
The second reason has to do with tokenomics. The L1 staking model gives the project’s token more obvious utility, as the token incentivizes the chain’s most crucial operations, and holders have sway over the chain’s direction and technical decisions.
L2s, on the other hand, greatly improve the profit-and-loss model for projects that want to monetize via fees. This arguably makes L2s the better choice for projects in gaming, consumer apps, and crypto-native DeFi. It's important to remember though that these are broad prescriptions – each project must carefully evaluate the options for its specific use case.
Bottom line: If credible neutrality and tokenomics are paramount to your project’s goals, the higher costs of an L1 may be worthwhile for you. If you primarily care about performance, optimization for a single app’s use case, or are primarily seeking to monetize through fees, then you should likely go with the lower-cost L2 model.
Need help evaluating the L1 vs. L2 decision for your project? Contact Conduit. We've launched more chains than any other infra provider and helped countless projects navigate these decisions.
End notes:
[1] L1 validator costs calculated based on chains' stated policies and dashboards from Dune and Token Terminal tracking chain metrics:
[2] L2 DA costs and data posting metrics pulled from L2Beat
[3] One note on ZK proving costs: ZK proof systems charge per validity proof, with each proof containing a number of transactions from a set time interval. Chains can customize this interval as needed. And the more transactions they fit into each interval (i.e. the higher their TPS), the less they pay per transaction. For ease of comparison though, we’ll run with Succinct’s $0.005 per transaction cost estimate, and our figure of $33.33 per MB of transaction data calculated from that estimate.