TLDR:
- Bittensor’s top 10 subnets reached a combined $550M valuation, reflecting strong ecosystem growth.
- Templar SN3 finished Covenant-72B using 72B parameters and 1.1T tokens without any central cluster.
- TAO token demand rises directly with subnet activity, as purchasing subnet tokens requires TAO first.
- Grayscale’s ETF filing and Jensen Huang’s comments signal rising institutional interest in TAO’s future.
Bittensor subnets have collectively reached a valuation of $550 million, drawing fresh attention to the TAO ecosystem.
Templar SN3 completed Covenant-72B, the largest decentralized large language model pre-training in history. The run used 72 billion parameters and 1.1 trillion tokens, with no centralized cluster involved.
This milestone has strengthened investor interest in both TAO and the growing subnet economy beneath it.
Covenant-72B Sets a New Standard for Decentralized AI Training
The Templar SN3 subnet trained Covenant-72B on 72 billion parameters and 1.1 trillion tokens. No centralized computing cluster was used throughout the entire training process.
The model’s performance is competitive with Meta’s LLaMA-2-70B in published benchmarks. This places decentralized pre-training on par with established open-source AI infrastructure.
Crypto analyst @ElCryptoDoc called the achievement “Bittensor’s DeepSeek moment” in a widely circulated post. NVIDIA CEO Jensen Huang also commented on the development, adding further visibility.
The comparison to DeepSeek reflects growing confidence in cost-efficient, distributed training methods. Industry observers have described the run as concrete proof point for decentralized AI.
Beyond Templar, Targon SN4 stands out as the highest-revenue subnet in the ecosystem. The subnet, operated by Manifold Labs, recently raised a $10.5 million Series A.
It serves real companies seeking confidential GPU compute through decentralized infrastructure. Chutes SN64, meanwhile, is expanding as a serverless inference and GPU compute option for developers.
These subnets operate across different layers of the Bittensor network but serve complementary purposes. Together, they show the ecosystem’s capacity for commercial use beyond speculative activity.
Developers are increasingly turning to decentralized alternatives for production AI workloads. This trend supports the credibility behind the $550 million combined valuation figure.
TAO Token Demand Strengthens as Subnet Activity Expands
A key mechanic in the TAO ecosystem ties subnet token purchases directly to TAO demand. Acquiring any subnet token requires TAO, making it the base currency across all subnets.
As subnet usage grows, so does the structural demand for TAO itself. This creates a compounding relationship between subnet performance and token value.
@ElCryptoDoc noted that one viral post about Templar drove TAO’s price up nearly 20% in a single day. That reaction shows how sensitive the market is to subnet-level progress.
Investors are treating individual subnet milestones as direct catalysts for the TAO token. The connection between the two layers is concrete and increasingly well-understood.
Grayscale has filed an ETF application tied to TAO, pointing to growing institutional interest. Jensen Huang’s public mention of Bittensor has also drawn attention from a wider investor base.
These external developments are positioning TAO within a broader AI-native asset conversation. TAO’s staking utility for subnets remains central to discussions around its long-term value.
As subnet competition intensifies, analysts are watching which networks will scale most effectively. Covenant-72B has established a measurable precedent for distributed model training at scale.
The $550 million valuation reflects current momentum alongside anticipated growth. The ecosystem now has tangible benchmarks to guide its next phase of development.
The post Bittensor Subnets Hit $550M Valuation as Covenant-72B Marks Decentralized AI Milestone appeared first on Blockonomi.
Source: https://blockonomi.com/bittensor-subnets-hit-550m-valuation-as-covenant-72b-marks-decentralized-ai-milestone/
