The Nakamoto Coefficient: A Measure of Decentralization
In 2017, Balaji Srinivasan, the former Chief Technology Officer at Coinbase and the mind behind the Network State concept, along with Leland Li, introduced a pivotal metric known as the Nakamoto coefficient. This measurement is designed to evaluate the level of decentralization within a blockchain network. Their research, presented in a paper titled “Quantifying Decentralization,” articulates the inherent risks of centralization, likening it to economic inequality through a unique approach that combines theoretical principles of both.
Understanding the Nakamoto Coefficient
The Nakamoto coefficient gauges the minimum number of entities—be it mining pools, validators, or other crucial players—that would be necessary to either disrupt or seize control of a blockchain network. By examining this coefficient, one can gain insights into how vulnerable a network might be to malicious attacks.
Key to the coefficient’s applicability is the understanding that it must consider the individual subsystems that make up a network. When analyzing popular public blockchains, distinguishing between the overarching system and its components is essential. For instance, in the case of Bitcoin, researchers identify six subsystems that play vital roles in its decentralization.
Real-World Examples: Bitcoin and Ethereum
To derive the Nakamoto coefficient for Bitcoin, one would take the lowest value from these subsystems. A clear example emerged as of May 1, 2025, when the introduction of the ViaBTC mining pool pushed the combined mining power of three dominant pools past the critical 51% level, yielding a Nakamoto coefficient of just 3. This finding underscores that even amid numerous nodes within Bitcoin’s framework, centralized mining pools can pose a significant threat to its security and decentralization.
Meanwhile, Ethereum, the second largest cryptocurrency, faces similar challenges in decentralization. While it boasts a considerable number of nodes, its Nakamoto coefficient stands at 5, largely due to the concentration of ETH staking power among a few major platforms including Lido, Coinbase, and Binance. Notably, the PoS (Proof of Stake) networks, such as Sui and Aptos, further complicate matters; these systems require a mere 66.6% majority of validators to authorize a block, creating risks of control for a small number of stakeholders.
Centralization in PoS Networks
As of the latest assessments, various PoS networks exhibit varying degrees of centralization, with Nakaflow reporting particularly low scores in some instances—Polygon shows just 4, while others like Solana and Cardano range from 20 to 35. Contrastingly, Polkadot’s parachain network remarkably leads the pack with a high score of 173.
The Future of the Nakamoto Coefficient
Some developers are adopting the Nakamoto coefficient as a framework for improving their blockchain technologies. The Internet Computer team, for instance, has proposed a modified approach to this metric within their documentation, arguing that merely relying on a minimum value may not effectively capture the nuanced risks within their architecture. The geographic distribution of node operators, for example, should not solely define collusion risks, hence the introduction of a weighted average approach. Their methodology illustrates that major shifts in the subsystem’s coefficient are more indicative of network resilience than minor increments.
Ultimately, the Nakamoto coefficient serves as a fundamental tool for measuring the necessary number of network participants which can efficiently govern and protect a blockchain. It provides a clearer view of power distribution and helps stakeholders assess both the safety and scalability of blockchain architectures. Nonetheless, this metric is not without its limitations, emphasizing the need for ongoing scrutiny and adaptation as the blockchain landscape continues to evolve.
