- Grayscale has filed an S-1 registration statement with the SEC to convert its Bittensor Trust into the first U.S. spot ETF for the TAO token, proposed to trade on NYSE Arca.
- The move follows the network’s first “halving” on December 14, 2025, which reduced daily token emissions from 7,200 to 3,600 TAO to increase scarcity.
- While the TAO token saw a 22% price drop immediately following the halving, it has recently stabilised around 222 dollars as institutional interest in decentralised AI infrastructure grows.
Grayscale has filed with the US Securities and Exchange Commission (SEC) to launch a TAO-linked product, in what would be the first US-listed exchange-traded product designed to give investors exposure to Bittensor’s token.
The company submitted a registration statement on Tuesday for the Grayscale Bittensor Trust (TAO). Grayscale said the ETF would list on NYSE Arca under the ticker GTAO. The filing names Coinbase Custody Trust Company and BitGo Trust Company as custodians.
Grayscale confirmed the filing in a post on X, describing it as an early step toward converting the trust into an exchange-traded product. Chairman Barry Silbert also posted that the move reflects the pace of development in decentralised AI.
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Grayscale Moves Forward With TAO
Grayscale’s Bittensor trust launched privately in 2024 and began trading more broadly via public quotation earlier this month.
The ETF filing comes shortly after Bittensor’s first halving in mid-December, which reduced the pace of new TAO issuance, similar in concept to Bitcoin’s scheduled supply cuts. TAO fell after the halving and has since stabilised around US$222 (AU$340), according to CoinGecko.
This filing basically puts Grayscale into an emerging, global race to list TAO-linked products. In Europe, Deutsche Digital Assets, a Germany-regulated exchange-traded products provider, has said it will list a Bittensor ETP on Switzerland’s SIX Swiss Exchange under the ticker STAO.
Bittensor is a decentralised network built around multiple application-specific subnets focused on AI workloads. Users earn TAO by providing computing resources that support those subnets.
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