The Wrong Reason TAO Is Rallying

BloFin Research213 FollowersFollow5ShareSavePlay(8min)CommentsSummaryThe training of the Covenant-72B model on distributed nodes validated decentralized AI model training and triggered TAO's recent rally.However, decentralized model training is unlikely to compete with frontier closed models: the physics of pretraining require co-located infrastructure that permissionless networks cannot match, and the open-weight market it can address is structurally self-diluting through distillation.Inference is different: modular, tolerant of hardware heterogeneity, and addressable by distributed supply, Bittensor's subnet Chutes (SN64) demonstrates a cost advantage over centralized aggregators and cloud standard tiers on open-model workloads. Just_Super/E+ via Getty Images On March 10, 2026, a team running on Bittensor's (TAO-USD) infrastructure completed training of Covenant-72B, a 72-billion-parameter model trained across more than 70 independent, globally distributed nodes. Ten days later, Nvidia CEO Jensen Huang referenced the achievement onThis article was written byBloFin Research213 FollowersFollowBloFin Research focuses on crypto research and analysis, dedicated to providing institutional-grade insights into the digital asset market. Our work covers major crypto assets, market trends from a macroeconomic perspective, and industry-wide studies on key developments shaping the digital asset ecosystem.