Bittensor's $TAO token economics are known for their simplicity, decentralization, and fair distribution. Unlike many other blockchain projects, $TAO tokens are not allocated to any party through ICO, IDO, or private placement, but are obtained through active participation in the network. This design not only reflects the principle of decentralization, but also ensures fair distribution of opportunities.
$TAO Token Allocation Mechanism
Decentralization and Fair Distribution: The distribution model of $TAO tokens is very simple, and all circulating tokens must be obtained through mining and verification. No tokens are obtained through pre-sales or private sales, which echoes the spirit of Bitcoin. The genesis casting of $TAO is consistent with the release schedule of Bitcoin, providing equal opportunities for anyone who contributes value to the network.
Mining and Validation: New $TAO tokens can only be generated through mining and validation. Each block rewards 1 $TAO token, which is equally divided between miners and validators. Therefore, the only way to obtain $TAO is to buy tokens on the open market or participate in mining and validation activities.
$TAO Token Uses
$TAO tokens have multiple uses in the Bittensor network, including governance, staking, participating in consensus mechanisms, and as a means of payment. Validators and miners stake their tokens as collateral to secure the network and receive inflationary issuance rewards. Users and businesses can use $TAO to access AI services and applications built on the network.
Governance and Staking: Users who hold $TAO tokens can participate in the governance and voting processes of the network, which allows them to have an impact on the future direction of the network. In addition, users can also stake $TAO tokens to validators to receive staking rewards.
Value Capture of $TAO Tokens
$TAO is the native token of the Bittensor network, and its intrinsic value is derived from its unique role in the ecosystem. Unlike the standard L1 model that derives value from selling block space, the value of $TAO is tied to the AI services it supports. As these services become more impactful and useful, the demand for $TAO increases.
Demand Drivers
Ecosystem Activity: Validators require $TAO tokens for registration, and users can purchase $TAO to participate in the voting process related to intelligence alignment and use as payment within the network.
Staking and Delegation: $TAO needs to be staked and delegated to earn staking rewards, which helps protect against inflationary issuance.
Speculative Premium: Betting on the upside potential of the convergence of two disruptive technologies such as blockchain and AI.
Network Effect: The network effect that results from more developers entering the network and leveraging the potential of the open source model.
Supply Drivers
Inflationary Emission: Total token issuance reaches 21,000,000.
Miners and Validators Sell Tokens: Miners and validators can sell $TAO tokens to cover operating expenses, similar to how Bitcoin miners sell Bitcoin to cover costs.
How to Get $TAO Tokens
In Bittensor, validators are incentivized to earn stakes from token holders, and this stake is essential for them to operate within the network. As a token holder, you can choose to delegate $TAO to a variety of different validators. The most common choice is the OpenTensor Foundation itself, which owns about 20% of the network.
Validator Rewards
Validators distribute 82% of their rewards to delegators in the form of $TAO tokens. Therefore, delegating $TAO tokens to a validator is an opportunity for token holders to earn staking rewards. This helps protect users from potential dilution caused by inflationary issuance of tokens.
Validator Rewards Currently 22.45%
Current Staking Rewards 18.41%
Risk vs. Reward
When evaluating the risk/reward of allocating a portion of your portfolio to $TAO, it is important to understand what you are actually buying. For example, the purchase does not entitle the holder to any form of yield paid in USD generated by the economic activity of the network. Instead, you receive token issuance as a reward. As a token holder, you can delegate these issued tokens to a validator to earn an annual interest rate and grow your $TAO holdings.
Analogy with Bitcoin
The analogy of $TAO to Bitcoin is clear, but there is an inherent story behind Bitcoin that makes it unique. No one has been able to provide a satisfactory answer to what the value of $BTC is or why it has any form of value, so the community has ended up in a tribal war between the haves, the “shitcoiners”, and the maximalists.
In fact, Bitcoin’s token economics are easy to understand: $BTC is used to incentivize miners to operate and maintain the network, so existing holders are diluted (although they can become miners or, in the case of Bittensor, delegators). Therefore, token holders are not incentivized and do not receive any rewards from the underlying network.
Scarcity vs. Decentralization: For $BTC, there is an important factor to consider, which is scarcity. The fact that there will only be 21 million $BTC makes it unique. While $TAO’s token economics is modeled after Bitcoin, there are still more than 70% of unissued tokens. This poses a dilemma for investors: do they value the decentralization of the network more, or the scarcity of the asset.
Conclusion: $TAO’s utility comes from the access it provides to AI models, governance uses, the opportunity to earn staking rewards, and the opportunity to act as an incentive mechanism. The current infrastructure construction costs are funded by the OpenTensor Foundation through delegation and delegation rewards. Other development is carried out by third parties who operate their own validator nodes, who are also funded through delegation.
Just as any global initiative requires funding for research, development, and deployment, the success of AI depends on how capital is coordinated and how stakeholders are rewarded for their contributions. It is this strategic allocation of resources (research, GPUs for training, etc.) that drives AI’s growth and impact.
In AI, especially large language models like ChatGPT, operating costs are very high. For example, OpenAI estimates that it costs about $700,000 per day to operate ChatGPT, which shows the high financial burden of large-scale AI models. The cost of training each model can range from millions to tens of millions of dollars, making it a more resource-intensive endeavor. The cost of training models on large datasets can be even higher, up to $30 million. While the company has raised significant funding, including a recent investment from Microsoft (roughly half in the form of Azure credits), the growing cost of training large language models remains a concern. Each training run costs millions of dollars, and the need to start from scratch for new models exacerbates the problem.
In this way, Bittensor not only embodies the principles of decentralization, but also ensures fair distribution and continued competition through the design of the $TAO token. This model not only contributes to the healthy development of the network, but also provides participants with a diverse incentive mechanism, further promoting the integration and innovation of artificial intelligence and blockchain technology.