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    τemplar

    SN3

    Evaluation Score

    Overall rating on a scale of 0-10

    RiskReturn
    04.510
    Risk Level:
    Very High
    Recommendation:Avoid
    Evaluated:August 27, 2026 (v14)

    Dimension Breakdown

    Development ActivityN/A
    Community HealthN/A
    Tokenomics4.5
    Market & Use CaseN/A
    Team & GovernanceN/A
    Security & AuditsN/A

    AI Analysis

    Comprehensive evaluation of the token

    SN3 (τemplar) operates as Subnet 3 on the Bittensor network, focusing on decentralized LLM pre-training. Across the evaluation, there is a severe data gap with five out of six sections (Active Development, Community Support, Market and Use Case, Team and Governance, and Security and Audit History) scoring -1.0 due to insufficient retrieval data and entity name collisions. The only scored section is Tokenomics at 4.5/10, reflecting high dilution headroom (~4x), structural inflation under the dTAO emission model, an absence of public vesting schedules, and severe 90-day price volatility (-79.80%). With Tokenomics carrying 100% of the redistributed weight, the final score is 4.5. No qualifying red-flag events or fraudulent mechanics were affirmatively established, but the pervasive lack of verifiable data across development, security, and governance introduces significant uncertainty.

    Development Activity

    Code updates and developer engagement

    Insufficient Data

    Community Support

    Social media presence and community engagement

    Insufficient Data

    Tokenomics

    Supply, distribution, and utility

    RiskReturn
    04.510

    Market & Use Case

    Value proposition and competitive landscape

    Insufficient Data

    Team & Governance

    Team background and project governance

    Insufficient Data

    Security & Audits

    Security history and audit status

    Insufficient Data

    About τemplar (SN3)

    τemplar (SN3) is a specialized subnet token operating as Subnet 3 within the Bittensor network. The project's core purpose centers on decentralized large language model (LLM) pre-training, which includes initiatives such as the Covenant-72B model. Operating natively within the Bittensor ecosystem, it utilizes the network's subnet infrastructure to coordinate and incentivize computational tasks related to AI model training.

    The tokenomics of SN3 are structured around the dynamic TAO (dTAO) emission mechanism, functioning as a yield-capture vehicle for subnet participants. It has a circulating supply of approximately 4.796 million tokens against a fully diluted valuation (FDV) of $107.31 million, representing roughly a fourfold dilution headroom. The asset is structurally inflationary through ongoing protocol emissions, and it operates without verifiable public vesting or token allocation schedules.

    SN3 has exhibited high market volatility, including a price decline of 79.80% over a 90-day period. Additionally, comprehensive evaluation of the project is constrained by limited public documentation regarding specific code repositories, developer activity, team identification, and dedicated third-party security audits.

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