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Compound V3’s documentation describes design choices intended to reduce gas, but it does not publish per-function measurements or a savings percentage. To find out what a transaction costs—or whether batching helps—measure the exact market deployment, implementation, chain, and transaction path you care about. A result from one Comet deployment is not automatically valid for another.
What Compound V3 does—and what its gas documentation establishes
Compound III, also called Compound V3 or Comet, lets users supply collateral to borrow a market’s base asset. Supplying the base asset can earn interest; collateral assets do not earn interest according to the Collateral & Borrowing guide.
The Compound III documentation says its protocol-configuration pattern “allows significant gas savings for users of the protocol by ‘constantizing’ the parameters of the protocol.” This is a qualitative design claim, not a measured estimate: the docs provide no per-function gas figures, comparative benchmark, or percentage. They also say deployment data on the overview page was collected on 2026-09-16 UTC, so verify current deployment and implementation details before relying on them.
The practical conclusion is that documented optimizations are hypotheses to validate against the code and bytecode you are auditing. Do not cite a general gas-saving figure for Comet unless it comes from reproducible measurements with a named implementation and environment.
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Establish the exact audit target first
Compound III has multiple network and base-asset deployments. Record the scope before measuring, and tie every result to the exact source and deployed code:
- Deployment: chain, market, base asset, Comet proxy, implementation, and any extension in scope.
- Build identity: source commit, compiler version and settings, and the deployed bytecode being evaluated.
- Transaction context: caller, account state, asset balances and approvals, manager permissions, and whether the call is a first-time or repeat operation.
The overview documentation distinguishes the stable proxy from its implementation, directs integrators to interact with the v3 proxy address, and says not to call the implementation directly. Confirm which implementation is behind the proxy at the time of the audit; do not treat an address list as proof of current implementation state.
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Measure the paths users actually execute
Measure successful transactions at the transaction level, with the chain and state conditions recorded. Separate cold and warm access conditions where relevant, and keep first-time and repeat operations distinct: they may touch different storage or follow different branches. A useful test matrix includes:
- ERC-20 approval followed by
supply, with first-time and repeat supplies tested separately. supplyToand manager-mediatedsupplyFrom, where the selected deployment and integration support those paths.withdraw,withdrawTo, and allowed-manager paths.- Borrowing, repayment by supplying the base asset, and cases around
baseBorrowMin. - Collateralized and reverting paths, including supply-cap and collateral-factor boundaries.
- Reward claims and transfers if they form part of the user flow being audited.
- Liquidator
absorbcalls across different account counts, plus a subsequent collateral purchase if that is in scope.
These methods and constraints are described in the supply and borrowing guide, liquidation guide, and helper documentation; those pages do not give their gas costs. Supply requires the relevant ERC-20 approval before the call. Withdrawals can remove collateral or borrow the base asset depending on the asset and account state. The initial borrow must meet baseBorrowMin, though later incremental borrowing may be smaller. A call that breaches collateral requirements can fail. Measure both the successful path and the boundary or failure path you intend to discuss rather than extrapolating from one transaction.
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Does Bulker save gas?
Bulker is an external contract whose invoke function accepts action codes and calldata and executes actions in sequence in one transaction. Compound describes it as useful for user interfaces. Its supported examples include supplying collateral and borrowing; the helper docs also describe native-token flows, transfers, withdrawals, and reward claims. The docs establish batching capability, not that a batch costs less gas than separate calls.
| Comparison point | Direct Comet calls | Bulker batch |
|---|---|---|
| Transactions | Separate direct calls may require multiple transactions for a multi-action outcome. | Can run multiple actions in one transaction. |
| What to compare | Measure the full sequence needed to reach the target end state. | Measure the same end state, including the batch’s calldata and any extra calls. |
| Gas savings | Not stated by the Compound III documentation; see overview and helper docs. | Not stated by the Compound III documentation; see overview and helper docs. |
For a fair comparison, use the same starting state and final outcome. Include approvals, manager authorization, token wrapping, and any external calls required by either route. Record calldata and revert behavior as well as gas. The documentation gives an example that wraps ETH, supplies WETH and WBTC, and borrows USDC; that example illustrates a possible batch, not a benchmark. Batching can change the number of transactions and user experience without guaranteeing lower total gas in every case.
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Inspect the storage and configuration claims in code
The helper documentation describes Comet’s UserBasic layout as containing principal, tracking indexes and accrued values, plus an assetsIn bitfield. It explicitly identifies this storage implementation as enabling gas savings, but does not isolate or quantify the effect.
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For the selected implementation, trace how the measured operations read and write those fields. Also inspect how that market’s generated implementation represents configuration and whether parameters are embedded as constants, as the overview documentation describes. Compare compiler output and deployed bytecode before attributing a gas difference to packing, bitfields, or constantized configuration. A code pattern alone does not establish the size of its effect on a particular transaction.
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Interpret liquidation accounting carefully
When borrow balance exceeds liquidation collateral limits, absorb transfers collateral and debt accounting to the protocol. The liquidation documentation says liquidatorPoints exposes numAbsorbs, numAbsorbed, and approxSpend; approxSpend is recorded as the sum of gas spent by a liquidator for successful absorb calls. It is accounting data, not a public benchmark or a promise of reimbursement. For an audit, measure the actual batch sizes and follow-on purchase path in scope rather than treating that field as a substitute for a benchmark.
Make results reproducible and comparable
- Pin the deployment and code. Record chain, market, proxy and implementation addresses, source commit, bytecode, and compiler/build settings.
- Define each scenario. Specify caller, account state, approvals and permissions, assets, call sequence, and whether storage access is cold or warm.
- Run equivalent paths. Compare direct calls with Bulker only when both produce the same end state; keep approval, wrapping, and authorization overhead in view.
- Record outcomes separately. Capture transaction-level gas for successful and reverting cases, and note which branch or boundary each scenario exercises.
- Limit each conclusion to its evidence. Do not compare raw totals across chains, implementations, compiler settings, or materially different states without explaining those differences.
The Compound III overview links to the Comet repository and lists third-party audit reports, but the existence of those reports alone does not establish their findings or version scope. Verify that any source or report used for comparison matches the deployment under review.
Use helper reads as diagnostics, not gas benchmarks
Comet helper reads expose balances, borrow state, asset configuration, prices, and protocol configuration. They are useful for establishing scenario inputs and checking account state. Unless the audit specifically examines on-chain composition, treat read-only calls as off-chain diagnostics; any measurement of an on-chain composed flow needs its own chain and call context.
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