Ethereum made transactions cheaper. Where does that leave ETH?
Ethereum has built a cheaper route for transactions through rollups and a separate market for their data, while an investment fund announced on November 12 has offered a different route to returns for ETH holders by combining staking with trading strategies, reopening the question of which parts of a growing Ethereum economy actually benefit the token.
- Sygnum’s November 12 announcement put its ETH fund’s annual return target at 8% to 10%, compared with its quoted staking range of 2% to 3%.
- A standard 21,000-gas ETH transfer burns 0.00021 ETH at a 10-gwei base fee, before any separate priority payment to a validator.
- Cutting that illustrative base fee from 10 gwei to 1 gwei requires 10 times as much identical gas usage to preserve the same burn.
- EIP-7918 uses an execution-cost parameter of 8,192 gas against 131,072 blob-gas units, establishing a reserve-price relationship between the two markets.
- Sygnum’s 8% to 10% objective is measured in ETH and includes staking, leaving investors exposed to changes in the token’s dollar price.
Sygnum’s announcement described a fund that keeps its core ETH holdings staked and uses options, arbitrage and derivatives funding strategies to seek additional income. Its target concerns the amount of ETH investors hold, not a guaranteed dollar return or a distribution of Ethereum’s total transaction fees.
The distinction arrives during an argument about the token’s economics. Ethereum co-founder Vitalik Buterin said on November 8 that the asset’s case should rest primarily on its qualities as a store of value, while keeping the network’s existing fee-burning mechanism.
Users, validators, rollup operators and investors receive different benefits from the same system. Following one payment through the fee rules explains why an application can become cheaper and more useful without passing an equivalent amount of income to everyone who owns ETH.
One Ethereum transaction pays for work, but the fee has two destinations
Ethereum’s gas documentation describes the fee as gas used multiplied by the base fee plus the priority fee. Gas measures the work performed, while the quoted price determines what each unit costs.
The base fee is destroyed under the protocol’s rules. The priority fee rewards the validator associated with including the transaction, so the user’s full payment should not be described as ETH burned.
For a simple transfer using 21,000 gas, assume a base fee of 10 gwei and a priority fee of 2 gwei. One gwei is one billionth of an ETH.
Multiplying 21,000 by 12 gives 252,000 gwei, or 0.000252 ETH, in total fees. Of that amount, 0.00021 ETH is the base-fee burn and 0.000042 ETH is the priority payment.
Converting the same transfer into dollars exposes a separate moving part. At an illustrative ETH price of $2,000, the 0.000252 ETH total costs $0.504, while the burned component is worth $0.42.
If ETH’s dollar price doubles and the gas inputs stay unchanged, the user pays $1.008 and the dollar value of the burn doubles to $0.84. The number of ETH destroyed remains 0.00021.
The calculation holds network demand constant to distinguish a token-price change from a change in the fee market. Reporting the doubled dollar burn as evidence that twice as much network service was purchased would confuse those two inputs.
The reverse can happen during a price decline. Dollar revenue can fall without a reduction in gas usage, while a fall in the base fee can reduce the ETH amount even if the dollar price holds steady.
A fee series can be examined in both units, provided the conversion uses the price for the relevant period. Using today’s price to value last month’s tokens answers what that quantity would be worth now, rather than what users paid at execution.
The example follows the units in the documentation and uses illustrative prices, not a November 13 fee quote. A contract interaction can consume a different amount of gas, so its bill requires its own gas-used figure.
At the same gas usage, lowering the base fee lowers the number of ETH destroyed. A lower dollar price for ETH can reduce the dollar value of the bill even if the number of tokens paid remains unchanged.
Those are two independent changes. A dollar-denominated fee chart combines the token price with the amount of ETH charged, while a supply calculation needs the actual token amount burned.
Ethereum’s EIP-1559 specification ties the base fee to demand for block space relative to a target. It was not designed as a fixed dividend rate for holders.
A maximum fee entered by the user is a spending ceiling, not necessarily the amount paid. The effective fee depends on the transaction’s execution and the prevailing base and priority components.
An unused gas allowance is different again. Setting a high limit does not mean every permitted unit is consumed, whereas execution that runs out of gas can fail while still charging for work performed.
For the owner of ETH, burning reduces the outstanding supply without making a cash payment into their wallet. Validators have a separate income stream, and applications can collect charges of their own above the network fee.
The accounting therefore starts with the receipt. How much gas was used, what base fee applied and what priority payment was made determine where that transaction’s payment went.
Rollups buy a shared data service instead of repeating every transaction on mainnet
Ethereum’s scaling design lets rollups process activity outside the base chain and publish information needed for Ethereum to support their security model. Different rollups use different methods for proving or challenging the resulting state.
The introduction of blobs through EIP-4844 provided a dedicated data channel. A rollup can put the data from many user transactions into a shared posting transaction instead of having each user independently purchase the same kind of mainnet execution.
The blob transaction specification gives blob gas a fee market separate from ordinary execution gas. Demand in one market therefore does not have to produce the same price movement in the other.
A user pays the rollup under its own charging rules. The operator then meets its Ethereum posting costs, along with the other costs of running the service.
The sum collected from users and the sum paid to Ethereum are different figures. An application can charge another fee on top, and a token traded on the rollup can have economics unrelated to either payment.
Batching changes the unit being sold. If a hypothetical operator pays 1 ETH to post a batch containing 100,000 comparable transactions, the average posting cost is 0.00001 ETH per transaction before its other expenses.
If the same posting bill can accommodate 200,000 transactions, that average falls to 0.000005 ETH. Total payment to Ethereum remains 1 ETH in the example even though twice as many users receive a transaction.
The calculation does not represent a particular live rollup. Compression, transaction complexity, capacity and posting schedules determine the number of transactions each real batch can accommodate.
It does show why a headline transaction count cannot by itself establish the base chain’s fee income. The reader needs the amount paid for the batches and the period over which they were posted.
A rollup can improve compression, making each transaction use less data. It can pass savings to users, retain part of them or use its pricing to compete for applications, subject to its own commercial arrangements.
Ethereum’s charge concerns the service purchased from Ethereum. It does not automatically capture the revenue an exchange, game or payment application earns from its customers on that rollup.
The network’s cheaper infrastructure and the application’s growth can thus appear in different accounts. Counting both user fees and the rollup’s Ethereum payment as independent base-chain revenue would count part of the same spending twice.
Ten times the activity is needed to offset a tenfold fee cut in a simple comparison
A useful way to examine the relationship is to hold the work constant. Take one million transfers, each using 21,000 gas, and give them an illustrative base fee of 10 gwei.
Their combined base-fee burn is 210 ETH. The method is one million multiplied by 21,000 gas multiplied by 10 gwei, then divided by one billion to convert gwei into ETH.
At 1 gwei, the same activity burns 21 ETH. Ten million otherwise identical transfers would be needed at the lower price to reproduce the 210 ETH burn.
The example measures gas expenditure, not adoption or a forecast for ETH. A million users making one transfer and one automated account making a million transfers could produce the same total under these assumptions.
It is equally important to hold the type of transaction constant. A change in the mix between simple transfers and complex contracts can change gas usage even if the number of transactions stays flat.
The calculation describes the revenue arithmetic behind fee reductions. Lower prices can support more activity, but the quantity purchased has to grow enough to offset the reduction before the total fee payment rises.
Rollup batching adds another variable. If each transaction needs less Ethereum data as well as cheaper data, user activity has to be compared with the operator’s actual posting bill, not just its own execution count.
The earlier fee-burn debate examined the decline after Ethereum provided cheaper data space. Its historical figures describe particular periods, not a fixed current burn rate that can be applied to November.
A daily annualization can create a different distortion. Multiplying one unusually busy day by 365 assumes that the same conditions persist through a year.
A comparable monthly or quarterly record needs the same observation period for issuance, burn and supply. The difference between issuance and burn can then be expressed in ETH before converting it into a percentage of supply.
Suppose an explicitly hypothetical month issues 80,000 ETH and burns 50,000 ETH. Net supply grows by 30,000 ETH, regardless of how many user transactions were necessary to produce that burn.
If burn reaches 90,000 ETH while issuance stays at 80,000, supply contracts by 10,000 ETH. Neither calculation alone supplies an ETH price because it does not specify buyers’ willingness to hold the resulting supply.
The token’s supply policy and its market valuation are connected through demand. They are not interchangeable measures of how well the network processed a particular month’s transactions.
The blob reserve price responds to execution costs, not a promised yield
EIP-7918 addresses a particular problem in the blob fee mechanism. Its authors describe circumstances in which other posting costs dominate the bill, leaving further reductions in the blob fee unable to attract much extra demand.
The reserve-price design connects the blob market to the cost of execution work. Its parameters include a blob base cost of 8,192 execution-gas units and 131,072 blob-gas units per blob.
Dividing 8,192 by 131,072 gives one sixteenth. The comparison places a reference value on blob gas relative to the execution base fee, while the algorithm governs how the blob price moves when the condition applies.
Calling it a fixed one-sixteenth charge on every transaction would be inaccurate. The mechanism concerns a blob and the fee-update calculation, not a universal retail price for each payment inside a batch.
For an illustrative execution base fee of 16 gwei, the 8,192-gas reserve value is 131,072 gwei, or 0.000131072 ETH per blob. At 1 gwei, the comparable reference value is 0.000008192 ETH.
Those calculations use the published constants with invented base-fee inputs. They show that the reference itself changes with execution conditions; it is not a dollar-denominated payment guaranteed to token holders.
The specification explains the adjustment as a way to make the blob fee market function when its own price is small relative to other costs. It does not set an annual minimum return for owning ETH.
Ethereum’s Fusaka specification includes EIP-7918 among the upgrade’s components. Capacity changes and pricing changes have to be examined separately because more available space can coexist with a different minimum pricing relationship.
Demand above the relevant target can still produce a different price from the reserve reference. Available capacity, posting demand and the timing of the adjustment affect the actual result.
A rollup’s bill can include execution fees, data fees and priority payments. Even an extremely low blob quote would not establish that the entire posting transaction cost nothing.
Comparisons between upgrades therefore need to use the same fee categories. A model estimating additional blob burn cannot be substituted for a measurement of total fees users paid across every application.
The economically relevant record is the amount actually paid under the active rules. The specification establishes how to interpret that record, while the network’s blocks supply the transactions needed to calculate it.
Staking pays participants, while net supply includes everyone
Ethereum replaced proof-of-work with proof-of-stake in September 2022. Its issuance explanation distinguishes new ETH issued to validators from ETH removed through transaction burning.
The page’s familiar 1,700 ETH daily issuance example assumes approximately 14 million ETH staked. Its text states that actual issuance changes with the amount staked, so that historical example should not become a current daily estimate.
A validator’s reward compensates participation in the consensus system. Holding an unstaked ETH balance does not entitle its owner to the same validator reward.
Burning, by comparison, reduces total supply. The unstaked holder participates in the resulting supply structure without receiving the burned tokens or a separate payment from the protocol.
The distinction explains why a staker can earn more ETH during a period in which total ETH supply rises. The reward paid to that participant and net issuance across the system answer different questions.
Sygnum put conventional staking rewards at approximately 2% to 3% annually in its November 12 announcement. The range is its dated comparison, not a permanent rate written into Ethereum.
Rewards depend on participation and the services used to stake. A provider can charge fees, a validator can incur penalties and a withdrawal can depend on the network’s applicable exit process.
A liquid-staking token creates another layer. Its holder has a claim defined by the staking arrangement and the token’s redemption mechanics, with a market price that can diverge from the value expected on redemption.
The number of ETH deposited in staking should consequently not be described as permanently destroyed. Staked principal and burned supply have different accounting treatment and different routes back into circulation.
Nor is a staking deposit necessarily a new purchase. An existing owner can move ETH already held into a validator arrangement, changing its use without producing a matching spot-market trade.
The same caution applies to an exchange-traded fund that begins staking an existing balance. Its activity may change income earned inside the product, while a fresh creation represents a different transaction.
Ethereum’s token can thus be bought, held as collateral, used for fees or committed to consensus. The quantity in any one category does not measure all sources of demand, and the same coins can move between categories over time.
Sygnum’s new fund separates earning ETH from betting on its dollar price
Sygnum’s November 12 announcement described an annual net return target of 8% to 10% in ETH. Its strategies combine staking with options premiums, arbitrage and derivatives carry or funding income.
As crypto.news previously reported, the fund opened to investors on November 2. Its quoted objective concerns the complete portfolio, not an additional 8% to 10% on top of staking rewards.
“Institutions that hold ETH for the long term increasingly think in ETH, not dollars,” Markus Hämmerli, Sygnum’s head of asset management, said in the announcement.
The bank describes the trading strategies as market-neutral while retaining directional ETH exposure in the fund. A strategy can seek income independent of the price direction without shielding the investor from the dollar value of the underlying ETH.
Consider an investor who starts with 100 ETH when the token is hypothetically worth $2,000. The initial dollar value is $200,000.
If the holding grows by 9% to 109 ETH but the token’s price falls 20% to $1,600, the ending value is $174,400. The investor owns more ETH and has a 12.8% dollar loss in that illustration.
The calculation multiplies 1.09 by 0.80 and subtracts one. It is not a prediction of the fund’s performance, and it assumes the stated 9% result has actually been earned.
The reverse works as well. More ETH can compound a dollar gain when the token rises, but neither outcome makes the fund’s return a payment from Ethereum’s transaction-burning mechanism.
An options premium comes from another market participant buying a contractual right. Arbitrage seeks a pricing difference between markets, while funding income arises from a derivatives position and its financing terms.
Each source carries obligations or risks alongside the receipt. Sygnum’s product information lists counterparty, staking, smart-contract, liquidity and trading-system risks, together with possible options losses and the effect of leverage.
Its fund terms set a $100,000 minimum investment or equivalent in ETH, monthly subscriptions and monthly redemptions with notice requirements. The bank names an investor-level gate of up to 10%, so the product is not an immediately redeemable wallet balance.
The fund is an example of the separate businesses forming around ETH ownership. Its performance will come from the implemented portfolio and its expenses, while Ethereum’s fee rules continue to determine issuance and burn outside it.
Buterin’s argument puts monetary demand ahead of maximizing fees
Buterin’s November 8 comments challenged the treatment of ETH as a predictable stream of burned fees. He argued that decentralization, censorship resistance, privacy and security supply a stronger foundation for the asset’s long-term appeal.
His store-of-value argument did not propose removing EIP-1559. It questioned whether maximizing fees should become the network’s overriding objective.
“EIP-1559 (including its burn) is fine and good, we should keep them,” he wrote. The distinction allows fee burning to continue without making a particular burn rate the network’s commercial target.
Buterin used a hypothetical $1 billion annual burn and a 4% discount rate to illustrate a $25 billion valuation. Dividing the assumed annual amount by the assumed rate produces that figure under a simplified perpetual-income calculation.
The calculation depends on the durability of the assumed fee stream. Buterin argued that activity linked to crypto speculation can weaken when token prices fall, making the income assumption less independent of the asset’s price than the model implies.
His argument is a position about valuation and network priorities. It does not establish that fees are irrelevant, or that a store-of-value description guarantees buyers will hold ETH at a particular price.
The strongest fee-based case starts with demand for services users are willing to buy. If settlement and data demand grow sufficiently, Ethereum can collect more fees even while remaining cheaper per transaction than a congested predecessor system.
The supply arithmetic allows that outcome. Higher aggregate gas demand or a higher market-clearing fee can raise burn, with the result depending on issuance over the same period.
A monetary case asks a different question: whether people want to hold ETH between transactions or use it as collateral and reserves. More efficient payments can require smaller working balances even while facilitating more transfers.
A business that settles frequently may purchase or retain only enough ETH to cover its next set of fees. Another participant may hold a substantial balance for collateral, without generating a comparable volume of transactions.
Neither behavior can be inferred reliably from a raw count of transfers. Net purchases, balances, collateral commitments and fees supply different parts of the demand record.
The disagreement therefore concerns which source of demand will sustain value over time. The fee model needs durable payments for scarce network services, while the store-of-value case relies on a durable preference to hold the asset itself.
Cheaper infrastructure leaves operators with their own bills
The economics of smaller rollups show another consequence of lower fees. Operators still pay for engineering, infrastructure, security and support even when their Ethereum posting bill falls.
A chain that charges little per transaction needs enough paying activity or another revenue source to meet those costs. Transaction growth can coexist with an operator losing money if the receipts do not cover its expenses.
A rollup token does not automatically entitle its holder to the operator’s surplus. The legal and technical arrangement determines whether the token supplies governance, fee utility, distributions or some other right.
Ethereum faces a related but distinct accounting question. It supplies settlement and data services, while consensus rewards and fee burning operate through protocol rules rather than a normal corporate income statement.
Applying a stock valuation directly to ETH requires specifying what the holder receives. A company shareholder may have a legal claim on residual assets and distributions; an unstaked ETH holder owns the token, with the protocol’s supply rules and available uses.
Sygnum’s fund supplies a contractual investment structure on top of that token. A rollup operator supplies another service, and an application can create a third business with its own customer charges.
Combining the revenues of all three would overstate what accrues directly to the ETH holder. Their payments may overlap, and the recipient of each fee has to be identified.
Future capacity depends on development decisions as well as demand. Ethereum’s Glamsterdam work includes changes to execution and gas accounting, with testing intended to establish how existing applications behave under the revised rules.
The Hoodi activation delay followed findings about assumptions embedded in smart contracts. The report identified eight affected invariants and the Ethereum Foundation’s request for developers to examine their own applications.
A proposed gas limit or an upgrade’s testnet activation does not establish the price users will pay on mainnet. Capacity, demand and the mix of operations determine the fee after deployment.
In its November 6 technical post, the Foundation said it was working with ChainSecurity and Dedaub on the effects of EIP-8037 and EIP-8038. The work concerned how charges for creating and accessing state interact with existing contract behavior.
The Foundation requested reports identifying affected contracts, the relevant invariant and possible fixes or supporting tests, with private submissions available for sensitive findings.
What to Watch
- Net supply: Issuance and burn measured over the same dated period, with the result expressed in ETH before annualization.
- Rollup payments: Execution and blob fees actually paid to Ethereum, compared with user activity over the same observation window.
- Staking returns: Rewards after provider fees and penalties, separated from trading income or a product’s targeted investment return.
- Holding demand: ETH balances used for collateral, reserves and staking, with transfers distinguished from newly executed purchases.
- Upgrade deployment: Confirmed mainnet specifications and activation notices for capacity and gas-accounting changes still under development.
FAQs
Why can more Ethereum transactions produce less fee burning?
A lower base fee reduces the amount burned for the same gas usage. Rollups can process more user transactions while sharing Ethereum posting costs across a batch. The total depends on both the price of the purchased service and how much of it operators use.
Does every part of an Ethereum transaction fee get burned?
The base fee is burned, while the priority component goes to the validator. At 21,000 gas, a 10-gwei base fee burns 0.00021 ETH. Adding a 2-gwei tip brings the total payment to 0.000252 ETH without changing that base-fee burn.
Does EIP-7918 guarantee that ETH becomes deflationary?
The mechanism links blob pricing to execution costs through a reserve-price relationship. Net supply still depends on total burn compared with issuance over the same period. Its published constants do not set a guaranteed annual burn or investor return.
Is staking income the same as a return from fee burning?
Staking rewards go to participants in consensus under the applicable rules and provider arrangements. Burning destroys ETH and affects total supply without paying a distribution to every holder. A staker can earn additional ETH during a period when overall supply is growing.
Is Sygnum’s 8% to 10% target on top of staking?
The fund’s product page describes 8% to 10% as the complete annual portfolio target after fees. It combines staking with options, arbitrage and derivatives strategies. The objective is not guaranteed and is measured in ETH, leaving investors exposed to the token’s dollar price.
Can an investor earn more ETH while losing dollars?
Yes. Starting with 100 ETH at $2,000, a 9% gain in coins produces 109 ETH. If the price falls to $1,600, the holding is worth $174,400, compared with $200,000 initially, giving a 12.8% dollar loss in that hypothetical example.
Has Vitalik Buterin proposed ending Ethereum’s fee burn?
His November 8 comments supported keeping EIP-1559 and its burn. He argued that ETH’s long-term investment case should focus on store-of-value properties and network reliability instead of maximizing fees. The distinction concerns priorities and valuation, not a stated proposal to abolish burning.
Which figures show whether Ethereum activity benefits ETH?
Fees paid to Ethereum, net issuance, staking rewards and holding demand answer separate questions. They should be measured over comparable periods, with application revenue kept separate from protocol payments. No single transaction count establishes a market valuation. This is educational analysis, not investment advice.
Disclaimer: This article is for information and educational purposes only and does not constitute financial or investment advice. Figures reflect regulatory filings and reporting available at the time of writing and change with each disclosure. Nothing here is a recommendation to buy, sell, or hold any security or asset. Always do your own research. Information is accurate as of November 13, 2026. Legal and tax questions should be discussed with qualified professionals.
