TAO Subnet Team Praised by Jensen Huang Has Parted Ways with Founder in a Bitter Split

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Remember the story where NVIDIA CEO Jensen Huang praised Bittensor (TAO)?

On March 20th, during an appearance on Chamath Palihapitiya’s All-In podcast, Huang was asked about his views on “decentralized AI systems/computing power networks.” Palihapitiya used Bittensor as an example (arguably with some self-interest), mentioning that a subnet team on Bittensor successfully trained a 4-billion-parameter (actually 72-billion-parameter) Llama model, with the entire process completed through distributed computing power collaboration. Upon hearing this, Jensen Huang commented that it was “a pretty remarkable technical achievement.”

Boosted by this positive news, TAO surged against the market trend last month, briefly surpassing $370, and Bittensor was hailed by the kriptocurrency industry as “the hope of the entire village.”

However, just half a month later, the situation took a sharp turn due to a sudden announcement — as of the morning of April 10th, TAO had fallen below $290, experiencing significant declines for three consecutive days, and Bittensor found itself embroiled in perhaps the biggest public relations crisis since its inception.

What Huang Actually Praised Was a Subnet Team Called Covenant AI

Before explaining the ins and outs of the incident, we need to first understand Bittensor’s subnet architecture.

Bittensor is a decentralized machine learning network centered around token incentives. Through its subnet mechanism, Bittensor allows different teams to build various AI task markets. Miners and validators participate in computation and evaluation, thereby distributing TAO rewards.

The “certain subnet team” mentioned earlier by Palihapitiya is actually called Covenant AI (formerly Templar). The model praised by Huang is called Covenant-72B. This is a 72-billion-parameter model collaboratively trained in a permissionless manner by over 70 independent contributors on general-purpose hardware, making it the largest decentralized large language model pre-training project in history.

In simple terms, Bittensor can be understood as the underlying infrastructure for projects like Covenant AI to operate on, responsible for providing incentives, governance, and network rules, rather than directly developing specific AI models or applications. Subnets like Covenant AI play a role more akin to “application-layer builders” that provide specific AI tasks and model capabilities on the underlying network.

Covenant AI’s Sudden Announcement

On the morning of April 10th, Covenant AI founder Sam Dare suddenly released a statement (considering TAO’s continuous decline, the underlying conflict may have been brewing longer), stating that due to Bittensor and its founder Jacob Steeves (online alias Const) betraying the principles of decentralization, Covenant AI has decided to exit the Bittensor network.

In the statement, Covenant AI pointed out that the team’s core belief is that “the training of frontier AI models should not be controlled by any single entity.” However, when a single actor can pause subnet emissions, override a subnet owner’s management rights over their own community space, publicly abandon projects without due process, and use token dumping as a coercive mechanism to force compliance, this is not decentralization but centralized control disguised as decentralization.

Covenant AI further alleged that every participant in the Bittensor ecosystem — miners, validators, and investors — should understand that this power indeed exists and has been exercised by Const. Const exercised this power not for the health of the network, but to regain control over a team that had become “too independent” and difficult to manage, a subnet owner capable of building its own community, making independent decisions, and operating permissionlessly, as this threatened his power within the entire ecosystem. Specifically, while Bittensor adopts a so-called “triumvirate” structure where three individuals manage network upgrades via multi-signature and claim it to the community as distributed governance, the reality is different. Const actually retains absolute power and resists any genuine transfer of authority — the power in the Bittensor ecosystem has never left one person’s hands.

Covenant AI also mentioned that over the past few weeks, Const has taken a series of actions against the team’s operations that conflict with the principles Bittensor claims to uphold, including pausing Covenant AI’s subnet emissions, removing the team’s administrative permissions for its own community channels, unilaterally abandoning subnet infrastructure, and exerting economic pressure through large-scale public token dumping during operational conflicts.

Therefore, Covenant AI has decided to exit the Bittensor network. The team concluded by stating that decentralized, permissionless AI training is not a feature unique to Bittensor, but a technological capability the Covenant AI team wishes to continue advancing. Covenant AI’s research, team, models, and vision will continue forward. Currently, there are very exciting projects in the pipeline, which will be announced to the public soon.

Conflict Goes Public, Bittensor Plunged into PR Storm

Due to the success of Covenant-72B (SubNet-3), and the fact that the Covenant AI team also operates two other key subnets — Basilica (SubNet-39, positioned as an AI model evaluation/inference-related subnet) and Grail (SubNet-81, positioned as a more complex task-driven AI subnet) — the team holds a pivotal position within the Bittensor ecosystem. Perhaps it was precisely Covenant AI’s growing influence in community, resources, and discourse that triggered the “power struggle” conflict with Const.

With the public airing of their conflict, the Bittensor ecosystem quickly plunged into a public relations storm.

On the product level, with Covenant AI’s departure, the community has begun to question the future development and value of the Bittensor network. As one of the teams with the strongest technical narrative and tangible results in the current Bittensor ecosystem, Covenant AI’s exit means this capability chain is being directly removed. Bittensor’s technical progress and ecosystem activity in the direction of AI model training face uncertainty, leading the market to adopt a more cautious stance regarding its long-term value.

Regarding reputational impact, Bittensor’s decentralization narrative is facing its biggest challenge since inception. Covenant AI’s accusations directly target Bittensor’s core narrative — the “decentralized AI network.” For Bittensor, which relies on its decentralization narrative to attract developers and computing power participants, the impact of this governance controversy far exceeds short-term price fluctuations and is more likely to shake the confidence of ecosystem participants.

On the brand level, Covenant AI has conversely used this controversy to gain an upper hand over Bittensor in the community’s perception. Prior to this announcement, the market’s general impression regarding “Huang’s praise” was that it was directed at Bittensor. Few realized that Covenant AI was the true protagonist, and not many even knew of the team’s existence. As the incident unfolds, Covenant AI’s visibility is continuously amplified, while Bittensor has become the party perceived by the community as “bleeding out.”

As of publication, Bittensor’s official social media channels have yet to comment. Const, on his personal account, gave a vague response: “This will push Bittensor to have its first truly ‘headless’ (likely referring to not relying on a single team), truly commoditized subnets… Thank you Covenant AI for making Bittensor more decentralized.”

Beneath Const’s response, a large number of Bittensor community users (especially TAO holders) are urging Const to provide more detailed answers to the allegations raised by Covenant AI, but Const has not yet responded further.

Odaily will continue to follow this matter. Stay tuned.

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