How to Design a Quadratic Voting System for Grant Prioritization

Quadratic Voting (QV) is a collective decision-making mechanism designed to capture the intensity of voter preferences, making it ideal for grant prioritization. Unlike one-person-one-vote, QV allows participants to allocate a budget of voice credits across multiple proposals. The key innovation is the quadratic cost function: the cost to cast n votes for a single proposal is n². This exponentially increasing cost prevents whale dominance, as it becomes prohibitively expensive for a single entity to concentrate all their influence on one option. This mechanism surfaces proposals with broad, moderate support over those with intense support from a small group.

Designing a QV system starts with defining parameters. You must set the total voice credit budget per voter (e.g., 100 credits) and the voting period. The frontend interface should clearly show the quadratic cost of additional votes. A critical implementation step is preventing Sybil attacks, where a user creates multiple identities to game the system. This requires a robust identity verification layer, such as proof-of-personhood protocols like Worldcoin or BrightID, or binding votes to a soulbound token (SBT) from a trusted registry. Without this, QV's fairness guarantees break down.

The core logic can be implemented in a smart contract. The contract must track each voter's remaining credit balance and calculate the cost of each vote action. For example, allocating 5 votes to a proposal would cost 5² = 25 credits. The contract validates that the cost does not exceed the voter's remaining balance before updating the proposal's vote tally and the voter's spent credits. After the voting period ends, the grant fund is distributed proportionally to the square root of the total votes each proposal received, aligning with the quadratic principle.

Consider this simplified Solidity code snippet for the vote function core logic:

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function vote(uint256 proposalId, uint256 voteAmount) public {
    uint256 cost = voteAmount * voteAmount; // Quadratic cost
    require(voiceCredits[msg.sender] >= cost, "Insufficient credits");
    require(!hasVoted[msg.sender][proposalId], "Already voted on this");

    voiceCredits[msg.sender] -= cost;
    proposalVotes[proposalId] += voteAmount;
    hasVoted[msg.sender][proposalId] = true;
}

Post-voting, calculate results using sqrt(proposalVotes[proposalId]) to determine each proposal's weighting for fund allocation.

Beyond basic implementation, key design choices impact outcomes. Use pairwise matching funds (like Gitcoin Grants) to amplify community support, where a central fund matches donations based on the QV results. Implement vote delegation for less engaged participants. Plan for batching and snapshotting to reduce gas costs on Ethereum L1, or build on a low-cost L2. Finally, conduct simulations with historical data to calibrate the credit budget and identify potential collusion or fraud vectors before launching a live round with real funds.

A quadratic voting (QV) system for grant prioritization requires a solid understanding of smart contract development and cryptographic primitives. You should be proficient with a language like Solidity or Vyper, and familiar with the EVM (Ethereum Virtual Machine) execution model. Experience with a testing framework such as Hardhat or Foundry is essential for writing secure, auditable contracts. You will also need a basic grasp of public key cryptography for signature verification, which is central to most on-chain voting mechanisms.

For the core QV logic, you must understand the mathematical formula: cost = (votes)^2. This non-linear pricing prevents Sybil attacks by making it exponentially expensive to concentrate voting power. You'll implement this using a credit-based system where participants receive a budget of voice credits. Each credit spent translates to a square root of the vote weight, so spending 4 credits grants 2 votes (sqrt(4) = 2). This requires fixed-point or integer math libraries, as Solidity does not natively support square roots or decimals.

Your development setup should include Node.js (v18+), a package manager like npm or yarn, and access to an Ethereum RPC endpoint. You can use a local node (e.g., Hardhat Network), a testnet provider like Alchemy or Infura, or a development suite from Tenderly or QuickNode. Essential tools include a wallet injector (e.g., MetaMask) for testing front-end interactions and a block explorer like Etherscan for verifying deployed contracts. Store environment variables securely using a .env file.

You will need to integrate with existing infrastructure. For identity and Sybil resistance, consider using ERC-20 tokens for stake-based eligibility, BrightID for social verification, or Gitcoin Passport for aggregated credentials. The system will also require an oracle or price feed if converting between currency and voice credits. For front-ends, familiarity with a Web3 library such as ethers.js or viem is necessary to connect the smart contract logic to a user interface.

Finally, plan your contract architecture. A typical QV system has separate contracts for: a Voting Contract to hold core logic and state, a Token Contract for credits or eligibility, and a Tally Contract to compute final results off-chain (using zk-SNARKs like Semaphore for privacy) or on-chain. Use upgradeability patterns (e.g., Transparent Proxy) with caution, and always include comprehensive event logging for transparency and easy result parsing by indexers like The Graph.

Quadratic Voting (QV) is a collective decision-making mechanism where participants allocate votes to proposals, but the cost of votes increases quadratically. A voter's cost to cast n votes for a single proposal is n². This design strongly penalizes concentrated voting power, making it economically irrational for a single entity to dominate the outcome. For grant prioritization, this means the community can signal the intensity of their preference for various projects without allowing whales or Sybil attackers to easily skew results. The core formula is expressed as Cost = (Number of Votes)² * Credit Cost, where credits are a budget given to each voter.

Designing a QV system requires several key components: a voter identity layer, a vote aggregation contract, and a cost calculation engine. The identity layer is critical for Sybil resistance; each participant should correspond to a unique human or entity, often verified through mechanisms like proof-of-personhood (e.g., BrightID, Worldcoin), social graph analysis, or bonded deposits. The voting smart contract must track each voter's credit balance and enforce the quadratic cost rule on-chain. A basic cost check in Solidity might look like:

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require(votesSquared <= remainingCredits, "Insufficient credits");

where votesSquared is the square of the new vote count for a specific proposal.

For grant programs, you must define the voting parameters: the total credit budget per voter, the voting period, and the proposal submission criteria. A common pattern is to allocate 100 budget credits to each verified identity. If a voter wants to cast 5 votes for a proposal, it costs 5² = 25 credits. They could then cast 4 votes for another proposal at a cost of 16 credits, using 41 credits total. The final tally for each proposal is the sum of the square roots of each voter's allocated votes, which translates back to the raw vote count. This ensures the aggregated result reflects the quadratic weighting.

Practical implementation challenges include front-running and gas costs. To prevent last-minute manipulation, consider using a commit-reveal scheme or closing the voting period with a snapshot. For scalability, you can compute the quadratic cost off-chain and submit a zk-SNARK proof of correct calculation, or use a Layer 2 solution. Always include a clear interface for voters to see real-time cost feedback and remaining credits. Tools like Tally or Snapshot with QV plugins can be integrated, but custom contracts offer more control over identity and anti-collusion logic.

The final step is result calculation and fund distribution. The proposal with the highest sum of square roots wins the primary grant slot. Some systems use QV to create a prioritized ranking for a funding committee or to automatically allocate a pool of funds proportionally. Post-vote, it's essential to publish the vote distribution and cost data for transparency, allowing the community to audit for potential collusion or identity system failures. This verifiable process makes QV a powerful tool for DAO governance, retroactive funding rounds like Gitcoin Grants, and public goods financing where fair preference aggregation is paramount.

Quadratic voting (QV) is a collective decision-making mechanism where participants allocate voice credits to express the intensity of their preferences. Unlike one-person-one-vote, QV uses a quadratic cost function: the cost to cast n votes for a single proposal is n². This design efficiently surfaces community consensus by making it expensive to concentrate all influence on a single option, thereby protecting minority interests. For grant programs, this helps prioritize projects that have broad, moderate support over those with intense support from a small faction. The core formula is implemented in the contract's voting logic.

The first step is designing the smart contract architecture. You'll need a GrantRound contract to manage the voting period, proposals, and the allocation of voice credits. Each voter receives an equal budget of credits (e.g., 99). A vote function should accept a proposal ID and a vote weight, then deduct weight² credits from the voter's balance. Use checks to ensure the voter has sufficient credits and the round is active. Store votes in a mapping like votes[roundId][voter][proposalId] = weight. The OpenZeppelin library is recommended for secure base contracts.

A critical challenge is Sybil resistance—preventing a single entity from creating multiple identities to game the system. Pure on-chain QV is vulnerable. The standard solution is to integrate a proof-of-personhood or unique identity system. You can require voters to hold a non-transferable Proof of Humanity profile, a BrightID verification, or a Gitcoin Passport with a minimum score. The contract should include a modifier that checks a verifier contract or an approved list of identities before allowing a vote. This ensures one-human-one-vote-credit-budget at the protocol layer.

After the voting round concludes, the contract must calculate the results. This involves summing the square roots of all vote weights per proposal: sum_of_sqrt_votes = Σ √(vote_weight). The proposal with the highest sum wins. This calculation can be gas-intensive on-chain. For efficiency, consider using an off-chain indexer (like The Graph) to query and compute results, or implement a commit-reveal scheme where votes are submitted as hashes and tallied in a separate transaction after the round ends. Emit clear events for each vote to facilitate off-chain tallying.

Finally, integrate the QV system into a full-stack application. The frontend should fetch active proposals and round data from your contracts, connect the user's verified identity, and provide an intuitive interface for allocating voice credits. Use a library like ethers.js or viem for blockchain interactions. Clearly display the quadratic cost (cost = weight²) as users adjust their sliders. After voting, show the user their remaining credit balance. For a complete reference, study existing implementations like RadicalxChange's QV contracts or Gitcoin's Grant Round infrastructure.

Quadratic Voting (QV) is a collective decision-making mechanism where participants allocate votes with a cost that increases quadratically. This means casting 2 votes costs 4 credits, and 3 votes costs 9 credits. It's designed to better reflect the intensity of voter preference and prevent whale dominance. In the context of a grant allocation DAO, QV allows community members to signal not just which projects they support, but how strongly they support them, leading to more nuanced and fair funding outcomes compared to simple 1-token-1-vote systems.

To implement QV on Snapshot, you must write a custom voting strategy. Snapshot strategies are JavaScript functions that run off-chain to calculate voting power. The core logic involves calculating the square root of a user's allocated voice credits to determine their actual vote weight per proposal. Below is a simplified strategy skeleton. The key function getVotingPower receives the user's address, a proposal choice, and their available voiceCredits (often a user's token balance).

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// strategies/quadraticVoting.js
export const author = 'your-handle';
export const version = '0.1.0';

export async function strategy(space, network, provider, addresses, options, snapshot) {
  // 1. Fetch user token balances (voice credits) for the snapshot block
  const balances = await fetchBalances(addresses, network, snapshot, options.address);
  
  // 2. Calculate quadratic voting power for each address
  const votingPower = Object.fromEntries(
    addresses.map((address) => {
      const credits = balances[address] || 0;
      // Quadratic formula: voting power is the square root of credits
      const power = Math.floor(Math.sqrt(credits));
      return [address, power];
    })
  );
  
  return votingPower;
}

In a real grant prioritization round, each voter receives a budget of voice credits (e.g., 99 credits). They can distribute these across multiple proposals. The strategy must also validate the vote within a proposal. A voter allocating 9 credits to a single proposal casts sqrt(9) = 3 votes for it. Your strategy's validate function must ensure the sum of the squares of votes per choice does not exceed the user's total credit budget, enforcing the quadratic cost constraint on-chain.

For production use, consider critical enhancements: - Sybil resistance: Integrate with proof-of-personhood or stake-based credit allocation. - Credit decay: Implement mechanisms like MACI (Minimal Anti-Collusion Infrastructure) to prevent collusion and bribery. - UI/UX: The Snapshot interface must be customized to show credit budgets and quadratic costs. The strategy's getVotingPower output directly feeds into Snapshot's vote tally, making the quadratic weighting automatic in the final results.

This QV strategy transforms Snapshot from a simple polling tool into a sophisticated grant prioritization engine. By moving the complex quadratic math into a verifiable, off-chain strategy, DAOs can implement fairer funding rounds that capture the nuanced will of their community, moving beyond mere token-weighted plutocracy.

Quadratic Voting (QV) operates on a simple but powerful principle: the cost of a vote increases quadratically with the number of votes cast on a single option. A user allocates a budget of voice credits (e.g., 100 credits) across multiple grant proposals. Casting 1 vote on a proposal costs 1 credit, 2 votes cost 4 credits (2²), 3 votes cost 9 credits (3²), and so on. This non-linear pricing forces voters to strategically distribute their influence, strongly supporting a few key initiatives they care deeply about rather than spreading votes thinly. It effectively measures the strength of conviction, making the aggregated result more reflective of collective welfare than one-person-one-vote systems.

Designing the system begins with defining the voting parameters. You must decide on the total voice credit allocation per voter, the voting period, and the proposal submission requirements. The core smart contract logic involves calculating the cost of a user's vote batch and ensuring they do not exceed their credit budget. A basic cost check in Solidity might look like:

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function _getCost(uint256[] memory votes) internal pure returns (uint256 totalCost) {
    for (uint i = 0; i < votes.length; i++) {
        totalCost += votes[i] * votes[i];
    }
}

The contract stores each voter's remaining credits and the cumulative quadratic votes (sum of sqrt(votes)²) for each proposal.

Result aggregation is the final and critical phase. Once voting concludes, you don't simply sum the raw vote counts. Instead, you calculate the quadratic score for each proposal by summing the square roots of the votes it received and then squaring the total: Score = (∑√votes_i)². This formula ensures the outcome is resistant to sybil attacks—a single entity splitting their credits into many identities gains less influence than a cohesive group. The proposals are then ranked by this score to determine funding priority. Implementing this off-chain via a snapshot of on-chain votes or in a contract's view function is standard practice to avoid high gas costs for complex math.

For grant programs like Gitcoin Grants, QV has proven effective in surfacing projects with broad, passionate support rather than those with a few wealthy backers. Key design considerations include preventing collusion through pairwise coordination and establishing clear rules for matching fund distribution based on the quadratic scores. Tools like MACI (Minimal Anti-Collusion Infrastructure) can be integrated to add privacy and reduce certain attack vectors. The final output should be a transparent, auditable ranking that the community perceives as legitimate, directing funds to the projects that create the most aggregate value as measured by the electorate's demonstrated preferences.

You now have the architectural blueprint: a system using commit-reveal schemes to prevent tactical voting, Sybil resistance through identity verification (like Gitcoin Passport or BrightID), and quadratic cost calculations to weight preferences. The critical next phase is rigorous testing. Deploy your contracts to a testnet (like Sepolia or Goerli) and simulate various attack vectors: front-running during the reveal phase, collusion among voters, and attempts to bypass identity checks. Use frameworks like Foundry or Hardhat to write comprehensive unit and integration tests.

For production deployment, consider the trade-offs between building a custom solution and using existing frameworks. Snapshot with its off-chain signing and flexible voting strategies can be a rapid starting point. For fully on-chain, transparent voting, a custom implementation using the OpenZeppelin Governor contract as a base, extended with your quadratic logic, offers maximum control. Key decisions include the token or credential used for voting power and the data availability layer for vote commits and reveals.

Beyond the core mechanism, focus on the user experience and governance lifecycle. Integrate with front-end libraries like wagmi and viem for seamless wallet connection. Design clear interfaces for proposal submission, voting, and result visualization. Establish an execution layer—often a multisig wallet or a DAO treasury module like Safe—to disburse funds to winning proposals automatically upon vote conclusion. Document the entire process for voters and proposers to ensure transparency and participation.

Finally, analyze and iterate. After each funding round, use the data to assess the system's health. Metrics to track include voter turnout, the distribution of voting power (Gini coefficient), and the correlation between project funding and subsequent impact. Use this feedback to adjust parameters like the matching pool size, the quadratic formula's constant, or the identity verification threshold. A well-designed quadratic voting system is not static; it evolves with its community.