Compound V3’s documentation describes design choices intended to reduce gas, but it publishes no per-function measurements or quantified savings. A useful gas audit therefore has to measure a specific Comet deployment and transaction path; claims about “Comet gas” in general are not meaningful without the chain, implementation, compiler settings, and state being compared.
What a Compound V3 gas audit can—and cannot—conclude
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, while collateral assets do not earn interest according to the Collateral & Borrowing guide.
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The official Compound III documentation says its configuration pattern “allows significant gas savings” by “constantizing” protocol parameters. That is a qualitative design claim, not a published benchmark: the docs do not state a gas figure, percentage saving, or per-function comparison. The same distinction applies to Comet’s storage layout and Bulker batching. You can investigate whether those choices matter for a particular implementation, but you should not present their benefit as measured until you have reproducible results.
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This article is an audit method, not a completed audit or report of tested transactions. Scope each conclusion to the source version and deployed bytecode you actually inspect.
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Which deployment and implementation are you measuring?
Compound III has multiple network and base-asset deployments. Start by identifying the market and the exact Comet instance: the chain, base asset, proxy address, implementation, any extension, and the source commit or verified source corresponding to the deployed bytecode. Compound’s documentation distinguishes the stable proxy from its implementation and directs integrators to interact through the v3 proxy—not to call the implementation directly. The overview’s deployment data is dated 2026-09-16 UTC, so check current deployment and implementation state rather than treating a documented address as timeless.
- Pin the build: record compiler version, optimizer configuration, and other relevant build settings for the implementation being analyzed.
- Match code to deployment: confirm that the source and build correspond to the bytecode behind the selected proxy. Avoid attributing a gas result to a source pattern that is absent from the deployed code.
- Keep the environment with each result: record chain, market, transaction path, account state, and whether storage and other accessed data are cold or warm.
- Keep comparisons like-for-like: raw gas totals across different chains, implementations, compiler configurations, or transaction states do not isolate the cause of a difference.
The overview links to third-party audit reports, but their version scope and findings should not be inferred from their existence. Read a report and verify that it covers the implementation under review before using it as evidence.
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Which transaction paths should you measure?
Measure complete, realistic paths as well as individual calls. A user’s total cost can include approvals, manager authorization, wrapping, helper calls, and separate transactions—not just the Comet method at the center of the operation.
Supply and borrowing
- Measure ERC-20 approval separately from
supply, then measure the combined user flow where relevant. ERC-20 callers must approve Comet before supplying. - Compare a first-time supply with a repeat supply to the same account and asset. Record the account and storage conditions that differ.
- Where relevant, measure
supplyToand manager-mediatedsupplyFromas distinct paths. - Measure borrowing and repayment by supplying the base asset. Include the initial-borrow boundary around
baseBorrowMin: an initial borrow must meet the minimum, while a later incremental borrow may be smaller. - Test valid and reverting cases around supply caps and collateral-factor requirements. A failed transaction can traverse a different path from a successful one, so report its gas separately and explain the tested boundary.
The method semantics and constraints above are described in the Collateral & Borrowing guide. The guide does not provide gas costs for these paths.
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Withdrawals, managers, and rewards
Measure withdraw and withdrawTo in the states that matter to the integration. A withdrawal can remove collateral or borrow the base asset depending on the asset and account state; a path that breaches collateral requirements can fail. If manager-mediated flows are in scope, include their authorization and call path rather than benchmarking only a direct account call. Measure reward claims and transfers only if they are part of the user journey being evaluated.
Liquidation and collateral purchase
When liquidations are in scope, measure successful absorb calls across batches with different account counts, then measure a subsequent collateral purchase if that is part of the same workflow. Liquidation is available when borrow balance exceeds liquidation collateral limits; absorb transfers collateral and debt accounting to the protocol. The Liquidation documentation describes liquidatorPoints fields numAbsorbs, numAbsorbed, and approxSpend. It defines approxSpend as the sum of gas spent by a liquidator for successful absorb calls. That accounting field is not a public benchmark and does not promise reimbursement.
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Does Bulker save gas?
Bulker is an external contract whose invoke method accepts action codes and calldata, then runs actions in sequence within one transaction. Compound describes it as useful for user interfaces and documents examples including supplying collateral and borrowing. The Helper Functions and Bulk Actions documentation also describes native-token flows, transfers, withdrawals, and reward claims.
Batching changes the transaction shape and can improve user experience by combining actions, but the documentation gives no gas comparison against separate calls. It does not establish that a Bulker flow is cheaper in every case. To test the claim, compare the same final outcome—not unlike workflows—using direct calls and Bulker.
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| Comparison | Direct calls | Bulker batch |
|---|---|---|
| Transaction count | Record each transaction required for the chosen flow. | Actions run in one invoke transaction. |
| Work included | Include required approvals, wrapping, authorization, and Comet calls. | Include the same prerequisites and all actions encoded in the batch. |
| Gas result | Sum transaction gas for the full end-to-end outcome. | Measure the full batch transaction, including its calldata and external calls. |
| Failure behavior | Record which transaction fails and whether earlier transactions already succeeded. | Record the batch’s revert behavior and whether the intended sequence completes. |
The documentation gives an example of wrapping ETH, supplying WETH and WBTC, and borrowing USDC. Use that kind of end-to-end flow only when it matches the market and user path under test; do not treat the example as a universal benchmark. Include calldata size, approvals, manager authorization, token wrapping, extra external calls, and failure behavior in the comparison. A single transaction may alter total cost and UX without guaranteeing lower gas for every case.
How should you test and report gas?
- Write down the question. For example, compare first-time and repeat supply, or compare a direct multi-step flow with an equivalent Bulker batch.
- Fix the target and setup. Name the chain, market, proxy and implementation, source version, compiler/build settings, account state, and transaction scenario.
- Separate path variants. Test cold and warm access conditions, successful and reverting cases, and relevant first-time versus repeat operations independently. Do not combine unlike paths into one average.
- Measure the full user outcome. Include approvals and any other required transactions or external steps. For Bulker, include the complete encoded action sequence.
- Repeat under controlled state. Make the account balances, permissions, collateral, and other relevant preconditions explicit so another engineer can reproduce the path.
- Report the boundary and result together. State what was measured, under which implementation and environment, and whether the number covers one transaction or an end-to-end flow. Keep failed transactions distinct from successful ones.
Read-only helper functions can expose balances, borrow state, asset configuration, prices, and protocol configuration. Treat these as off-chain diagnostics unless the audit specifically evaluates their on-chain composition; include chain and call context for any measurements. The helper documentation explains the available helpers but does not provide gas costs.
How to evaluate Comet’s storage and configuration claims
The Helper Functions documentation describes Comet’s UserBasic layout as including principal, tracking indexes, accrued values, and an assetsIn bitfield, and says this storage implementation enables gas savings. It does not publish an isolated measurement. Inspect the selected implementation’s reads and writes to those fields along each measured path; the existence of packed fields alone does not tell you the transaction-level saving.
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Likewise, inspect how the selected market’s configuration is represented in the generated implementation. The overview attributes gas savings to parameters being constantized. To support an implementation-specific conclusion, verify the compiled output and deployed bytecode, then connect the observed gas difference to the code path you measured. Documentation supports the design rationale; only scoped code review and measurements support a concrete gas conclusion.
Quick Recap
What belongs in the final audit finding?
- Target: chain, market, base asset, proxy and implementation, source version, and compiler/build configuration.
- Scenario: the exact user operation, prerequisites, account state, success or failure condition, and cold/warm assumptions.
- Measurement: transaction-level result or end-to-end total, with the scope of the number stated alongside it.
- Comparison: equivalent outcomes and explicit differences in transactions, calldata, approvals, authorization, wrapping, and external calls.
- Interpretation: distinguish an observed result for this deployment from a general protocol claim. Treat documentation statements about constantized parameters, storage layout, and batching as design descriptions unless your own measurements establish their effect.
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