Bittensor’s TAO is up 90% so far this month, and tokens in its ecosystem are rising even more.
The network’s subnet token category reached a combined market capitalization of $1.47 billion on Monday, with $118 million in 24-hour trading volume, according to data from CoinGecko.
The rise follows TAO’s own run from $180 to over $332 in March, but subnetwork tokens are where the real action is. Subnet 3 token Templar gained 444% in 30 days. OMEGA Labs rose 440%. Level 114 added 280%. BitQuant gained 230%. Even the largest subnetwork tokens posted significant returns, with Chutes rising 54% and Targon gaining 166%.
Bittensor is a decentralized network that creates markets for artificial intelligence. Instead of one company building and controlling AI models, Bittensor incentivizes a global network of participants to contribute computing power, data, and machine learning models in exchange for TAO, the network’s native token.
The network is divided into specialized subnets called subnets, each of which focuses on a different AI task, from training language models to running computing infrastructure and cybersecurity analysis. There are currently 128 active subnetworks, each with its own token whose value is directly related to the amount of TAO staked on it.
Several catalysts contributed to these movements of Bittensor ecosystem tokens.
Subnet 3 produced Covenant-72B, a large language model trained permissionlessly on the Bittensor decentralized network by over 70 contributors using commodity Internet hardware.
The model was trained on 1.1 trillion tokens and achieved a score of 67.1 MMLU, confirmed in an arXiv paper from March 2026. That puts it in competitive range with Meta’s Llama 2 70B, a model built by one of the best-resourced AI labs in the world. (MMLU, or Massive Multitasking Language Understanding, is a standardized test for AI models that scores them in 57 academic subjects.)
Subnet 3, called Templar, is Bittensor’s decentralized AI training network. Miners contribute GPU computing power and compete to produce useful training gradients for large language models, while validators evaluate the quality of their contributions and distribute TAO rewards accordingly.
Think of it as a way to train AI models in the same way as Bitcoin mining blocks, with participants distributed around the world contributing hardware and getting paid for useful work.
Separately, Nvidia CEO Jensen Huang and investor Chamath Palihapitiya backed Bittensor’s approach on the March 20 All-In Podcast, framing decentralized AI training as complementary to proprietary models. Coming from the CEO whose blog post earlier this month briefly helped reverse a sell-off in tech stocks, the endorsement carried weight beyond the usual crypto echo chamber.
How subnet tokens work
The mechanics of the subnet token explain why the gains are so huge compared to TAO itself.
Since Bittensor launched dynamic TAO in February 2025, each subnetwork operates its own automated market maker with a native token whose valuation is determined by the TAO staked in that subnetwork’s reserves. When TAO appreciates, each subnet’s reserve becomes more valuable, inflating token prices and attracting more participants. The relationship is reflexive and amplifies movements in both directions.
With TAO having approximately $3 billion in market capitalization and individual subnetwork tokens ranging between $1 million and $137 million, subnetwork tokens function as leveraged bets on the main protocol.
The network plans to expand from 128 to 256 active subnets later this year, which would bring a new wave of token launches.
A potential regulatory decision on converting Grayscale TAO Trust into a spot ETF could provide institutional access as early as late 2026. And Digital Currency Group subsidiary Yuma is already contributing to 14 different subnetworks, suggesting the smart money is treating this as infrastructure rather than speculation.
Whether the subnet’s rally holds depends on whether Bittensor continues to produce competitive AI models or whether Covenant-72B was a one-off product that got lucky with Huang’s backing.
