Burn-and-Mint

Burn-and-Mint is a token supply control mechanism where a protocol burns (permanently destroys) a base-layer token, like Ethereum (ETH), to mint (create) a new application-specific token. This model creates a direct economic link between the two assets, often making the minted token's value contingent on the demand to use the underlying service. The process is governed by smart contracts that verify the burn transaction on the base chain before issuing the new token, typically on a separate chain or layer-2. This mechanism is foundational to projects like OMG Network (now Boba Network), which pioneered its use.

The model's primary function is to align network security with utility. Burning the base asset (e.g., ETH) transfers economic value and security assumptions from the established parent chain to the new ecosystem. The minted token is then used to pay for services, govern the protocol, or stake for rewards within its own network. The burn acts as a fee or toll for accessing the new chain's capabilities, while the mint rewards validators or provides the medium of exchange. This creates a sustainable economic loop where increased usage of the application leads to more burns, which can theoretically increase the scarcity and value of the base asset being consumed.

A key implementation is the Burn-and-Mint Equilibrium (BME) model, which aims for a stable token supply. Here, the protocol algorithmically adjusts the mint rate based on network usage to target a specific circulating supply of the new token. If usage is high, burning exceeds minting, making the new token deflationary. If usage is low, minting may exceed burning. This feedback loop is designed to incentivize usage and stabilize the token's value over time without requiring continuous inflationary emissions.

Burn-and-Mint is often contrasted with Stake-for-Service or Proof-of-Stake models. While staking locks assets temporarily, burning destroys them permanently, creating a stronger sink for the base asset. This model is particularly suited for Layer-2 scaling solutions and application-specific chains that want to leverage the security of a major blockchain like Ethereum while fostering their own independent token economy. It solves the 'security budget' problem by forcing the application chain to continuously purchase security from the base layer via burns.

Critically, the model's success depends on sustained demand for the application's services to justify the continuous burn of valuable assets. If utility demand falters, the minted token may lose its value anchor. Furthermore, the regulatory treatment of the minted token can be complex, as its creation is directly tied to the destruction of another cryptoasset. Despite these challenges, Burn-and-Mint remains a sophisticated template for bootstrapping cryptoeconomic security and creating interlinked token ecosystems.

The burn-and-mint mechanism (BME), also known as the burn-and-mint equilibrium, is a dual-action cryptographic economic model that regulates a network's native token supply by programmatically burning a portion of transaction fees and subsequently minting new tokens as protocol rewards. This creates a dynamic equilibrium where the net token supply is controlled by the balance between the burn rate (destruction) driven by network usage and the mint rate (issuance) determined by protocol rules. The primary goal is to align token value with underlying utility, as increased demand for network services leads to more tokens being burned, creating deflationary pressure that can be offset by controlled, predictable minting to reward validators or service providers.

The mechanism operates on a continuous loop. First, users pay for network services (e.g., data storage, oracle feeds, compute) using the native token or a stablecoin. A significant portion of these fees is permanently destroyed or burned, removing them from circulation. Second, the protocol mints new tokens according to a predefined schedule or formula, often distributing them to node operators, validators, or stakers who secure and service the network. The minting rate is typically algorithmically adjusted, sometimes targeting a specific velocity or a stable token price relative to the cost of the service provided. This feedback loop ensures that token issuance is directly tied to proven, paid-for demand.

A canonical example of this model is the Threshold Network with its tBTC and keep systems, and Helium Network's transition to the IOT and MOBILE tokens. In these systems, the burn rate acts as a verifiable signal of real economic activity. If usage spikes, burning accelerates, making the existing token supply scarcer. The protocol may respond by increasing minted rewards to incentivize more service providers, expanding network capacity to meet demand. Conversely, low usage reduces burning, prompting the protocol to slow minting to avoid excessive inflation. This creates a self-regulating economic flywheel distinct from simple inflationary proof-of-stake rewards or rigid fixed-supply models.

Key design parameters include the burn ratio (percentage of fees destroyed), the mint cap (maximum issuance rate), and the target equilibrium price. Developers must carefully calibrate these to prevent hyperinflation from excessive minting or stagnation from insufficient rewards. The model inherently shifts value accrual from pure speculation to utility consumption; the token's value is backed by the cumulative cost of all burned tokens, representing sunk cost in network usage. This makes it particularly suited for utility networks and oracles where service demand should directly influence the supporting token's economics.

Compared to pure burn models (e.g., EIP-1559) or pure mint models, the burn-and-mint equilibrium offers a balanced approach for provisioning networks. It ensures service providers are compensated with newly minted tokens, funding network security and growth, while the burn function imposes a cost on usage that stabilizes or increases the token's value for holders. Successful implementation requires robust, tamper-proof oracles to measure usage metrics and a transparent, governance-managed policy for adjusting mint rates in response to long-term burn trends, ensuring the system remains sustainable and resistant to manipulation.

The Burn-and-Mint Equilibrium (BME) is a tokenomic model where a protocol burns (permanently destroys) tokens paid as network fees and subsequently mints (creates) new tokens to reward service providers, aiming for a net-zero inflationary effect over time. This creates a circular economy where token utility directly influences its supply. The core mechanism involves users burning tokens to access services, which reduces circulating supply, while the protocol mints new tokens to pay node operators or validators, which increases it. The intended equilibrium is reached when the burn rate equals the mint rate, stabilizing the token's circulating supply.

The flow begins when an end-user, such as a developer querying a decentralized data network, pays for the service using the protocol's native token. These tokens are sent to a verifiably unspendable address or a smart contract that irrevocably destroys them, an on-chain event known as a burn. This action reduces the total and circulating supply of the token, applying deflationary pressure. The value of the burned tokens represents the protocol's captured revenue and is a direct measure of real economic activity and demand for the network's core utility.

Simultaneously, the protocol mints new tokens according to a predefined emission schedule or a formula tied to usage. These newly minted tokens are distributed as rewards to the network's service providers—like node operators who index data or relay transactions—who are essential for the network's operation and security. This minting introduces inflationary pressure. The critical design goal is to algorithmically or parametrically adjust this minting so that, over a given period (e.g., an epoch), the amount minted approximates the amount burned, leading to a supply-neutral or controlled-inflation outcome.

Visualizing this as a closed-loop system highlights its self-regulating nature. High network usage leads to more burns, which can outpace minting, creating deflationary scarcity. If usage drops, minting may temporarily exceed burning. Sophisticated BME models may include staking requirements for service providers, where operators must lock tokens as collateral, and fee models that dynamically adjust based on congestion. This interplay between burn-driven deflation and reward-driven inflation seeks to align the incentives of all participants—users, service providers, and token holders—around the long-term health and utility of the network.

A canonical example of this model is the Graph Protocol, which uses BME for its GRT token. Indexers stake GRT to provide indexing and querying services, while consumers (users) pay query fees in GRT that are burned. The protocol mints new GRT as rewards for indexers and other network participants. The parameters governing minting and burning are set by protocol governance, allowing the community to calibrate the equilibrium in response to market conditions and growth objectives, making BME a dynamic and governable economic primitive.