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Bittensor
TAO

Bittensor

$201.26
5.92%
Market Cap. #36
$2,210,227,806
Volume (24h) #32
$244,550,382
Supply (Circ. / Total / Max)
10.98M / 10.98M / 21.00M
  • Overview
  • News
  • Markets
Bittensor Logo

BittensorTAO

TAO

$201.26
5.92%
  • Overview
  • News
  • Markets
Loading chart...
Market Cap. #36
$2,210,227,806
Volume (24h) #32
$244,550,382
Supply (Circ. / Total / Max)
10.98M / 10.98M / 21.00M
Launch Date
2023-03-20
Block Number
8,338,628
Block Reward
-
Last Block Size
-
Network H/s
-
2023-03-20
Launch Date
8,338,628
Block Number
-
Block Reward
-
Last Block Size
-
Network H/s

Bittensor Price Converter

Bittensor

Bittensor Information

Resources

Websites
bittensor.comWhitepaper
Block Explorers
taostats.io
Industries

Research Reports

Digital Assets: Quarterly Review and Outlook Q1
Featured

Digital Assets: Quarterly Review and Outlook Q1

Apr 10, 2026
The $19 Billion Liquidation That Shook Crypto

The $19 Billion Liquidation That Shook Crypto

Oct 17, 2025

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Bittensor Markets

About Bittensor

Bittensor (TAO) is an ERC-20 token powering a decentralized, blockchain-based machine learning network. Models train collaboratively and are rewarded in TAO for their informational value. Bittensor is an open-source protocol leveraging a distributed ledger to develop and distribute AI technology efficiently. It promotes open access/ownership, decentralized governance, and harnesses globally-distributed resources within an incentivized framework. TAO is used to reward models and grant external access to the network. The team behind Bittensor includes founders Jacob Steeves and Ala SHaabana, Director of Marketing Jacqueline Dawn, and Blockchain Architect Saeideh Motlagh.

Bittensor is a decentralised blockchain network designed to enable the collaborative creation, training, and evaluation of artificial intelligence (AI) models. It operates as a peer-to-peer intelligence marketplace where participants, referred to as miners and validators, interact within subnets to produce and assess machine intelligence outputs. Each subnet focuses on a specific AI task or data type, such as text, images, or other modalities, creating a decentralised environment for AI development.

Bittensor’s protocol uses its native blockchain to record interactions, rank participants, and distribute rewards in the form of TAO tokens. Validators evaluate the outputs of miners and assign scores based on performance. The network incentivises participants by rewarding contributions that provide information-theoretic value. This design fosters an open ecosystem for AI research and development without relying on centralised authorities.


TAO is the native cryptocurrency of the Bittensor network and has multiple use cases:

  • Incentives and Rewards: Validators and miners are rewarded with TAO tokens based on their contributions within subnets, including generating or evaluating AI outputs.
  • Staking: Participants stake TAO tokens to support the security and operation of subnets. Stakers earn rewards proportional to their contributions and the performance of the subnet.
  • Governance: TAO token holders can vote on governance decisions that affect the network, such as protocol updates or changes to incentive mechanisms.
  • Transaction Fees: TAO tokens are used to pay transaction fees for activities on the blockchain.
  • Subnet Deployment: Subnet operators utilise TAO to establish and maintain subnets, including computational infrastructure and reward distribution.

Bittensor was developed by the Opentensor Foundation, a non-profit organisation focused on decentralising AI development and enabling collaboration in machine learning. The core team includes Jacob Robert Steeves, Ala Shaabana, and Saeideh Motlagh.

Bittensor facilitates the decentralised creation and deployment of AI systems through its blockchain infrastructure. Its key features include:

  • Peer-to-Peer Collaboration: Participants interact within subnets to exchange AI outputs, evaluate performance, and collaboratively train models.
  • Incentive Mechanisms: Validators and miners are rewarded with TAO tokens based on their contributions to the network, with a focus on informational value and performance.
  • Subnet Flexibility: Subnets are tailored for specific tasks or data modalities, enabling a diverse range of AI applications and use cases.
  • Security and Fairness: The network employs ranking and incentive systems to discourage collusion and ensure equitable distribution of rewards.

This structure supports an open, decentralised approach to AI development, promoting accessibility and innovation across a global network of participants.


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