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Bittensor Protocol: The Bitcoin in Decentralized Artificial Intelligence? A Critical and Empirical Analysis

In: Mathematical Research for Blockchain Economy

Author

Listed:
  • Elizabeth Lui

    (FLock.io)

  • Jiahao Sun

    (FLock.io)

Abstract

This paper investigates whether Bittensor can be considered the “Bitcoin of decentralized Artificial Intelligence” by directly comparing its tokenomics, decentralization properties, consensus mechanism, and incentive structure against those of Bitcoin. Leveraging on-chain data from all 64 active Bittensor subnets, we first document considerable concentration in both stake and rewards. We further show that rewards are overwhelmingly driven by stake, highlighting a clear misalignment between quality and compensation. As a remedy, we put forward a series of two-pronged protocol-level interventions. For incentive realignment, our proposed solutions include performance-weighted emission split, composite scoring, and a trust-bonus multiplier. As for mitigating security vulnerability due to stake concentration, we propose and empirically validate stake cap at the 88nd percentile, which elevates the median coalition size required for a 51% attack and remains robust across daily, weekly, and monthly snapshots.

Suggested Citation

  • Elizabeth Lui & Jiahao Sun, 2026. "Bittensor Protocol: The Bitcoin in Decentralized Artificial Intelligence? A Critical and Empirical Analysis," Lecture Notes in Operations Research, in: Stefanos Leonardos & Amir K. Goharshady & William Knottenbelt & Panos Pardalos (ed.), Mathematical Research for Blockchain Economy, pages 145-165, Springer.
    • Handle: RePEc:spr:lnopch:978-3-032-13377-9_7
    DOI: 10.1007/978-3-032-13377-9_7
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