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TAO How Bittensor allocates $TAO between AI subnets
Bittensor is a decentralized network whose core is built around competing AI subnets. Each subnet focuses on a specific digital good: computing power, reasoning services, storage or prediction. In order to support this competitive mechanism, the agreement will continue to mint new $TAO tokens.
Every day, 3,600 additional $TAOs are added to the Internet, which is equivalent to 0.5 $TAOs issued every 12 seconds. These tokens are then allocated to active subnets, but not equally. Bittensor uses a price-based model to determine the distribution ratio of $TAO between subnets. Each subnet's share of the block issuance is proportional to its exponential moving average (EMA) token price and normalized for all subnets with additional issuance enabled.
In other words, the market demand for work on a subnet directly determines the benefits of that subnet. For those subnets that attract real demand, the token price will rise, thereby gaining a larger proportion of additional issuance shares. However, price is not the only factor determining the outcome. The agreement uses an "Emission Gate" mechanism to significantly reduce the share of weaker or depressed subnetworks, concentrating rewards where actual output is generated.
The V440 version of additional issuance gating introduces a stricter subnet reward framework to guide additional issuance based on performance and needs rather than allowing weak subnets to occupy the same economic weight. The newly established subnet also faces a deliberate climbing period of about four weeks, which weakens the impact of speculative start-ups on additional issuance allocation.
Allocation mechanism of rewards after entering a subnet
Once a subnet's share of the block reward is determined, the allocation within that subnet follows a fixed structure. The $TAO cast for each block is distributed in the following proportions: 41% is given to AI miners (responsible for running reasoning), 41% is given to verifiers (responsible for scoring work), and 18% is attributed to subnet creators.
The verifier scores the miners 'output and submits the evaluation results to the chain. According to the Yuma consensus algorithm, the validator's score on the performance of the miners determines the allocation of additional issuance quotas among the miners. This design is designed to achieve self-correction: if a malicious verifier's score deviates too much from the consensus, its benefits will be reduced and diluted over time by honest verifiers.
In addition, as the operating time of the subnet increases,$TAO that can no longer be injected as liquidity will be exchanged for Alpha tokens in the subnet's own pool, creating buying pressure. This mechanism has prompted mature subnets to shift from liquidity injection to on-chain repurchase. The end result is that funds flow to AI services that are truly recognized by the market, rather than being allocated by committees or predetermined formulas.
