Decentralization and the Core Value of Blockchain

One of the core values of blockchain technology is decentralization. It ensures the system’s security, resistance to censorship, and fairness by allowing transaction records and decision-making power to be maintained collectively, rather than being controlled by a single centralized entity. In contrast, traditional centralized systems—such as banks, social media platforms, and cloud services—may operate with greater efficiency but are vulnerable to single points of failure (SPOF), data monopolies, censorship risks, and high trust costs. For example, banks can restrict access to funds, social platforms can delete content at will, and technical failures at cloud service providers may result in large-scale service disruptions.

These risks have led to the rise of blockchain technology, which reduces dependence on centralized authorities through decentralized architecture, enhancing transparency and security.

However, decentralization is not binary—it exists on a spectrum. Some blockchains may be dominated by a few mining pools or controlled by a small number of validators who hold the majority of staked tokens. This concentration of power undermines both the system’s resistance to attacks and its fairness. As a result, accurately measuring a blockchain’s degree of decentralization becomes a critical issue.

To address this challenge, the Nakamoto Coefficient was introduced. This metric quantifies the level of decentralization in a blockchain by indicating the minimum number of independent entities required to disrupt the system’s operation. The higher the coefficient, the more distributed the power, and the greater the degree of decentralization. Conversely, a low coefficient suggests power is overly concentrated, making the network more susceptible to manipulation or attack. For instance, in a blockchain where only three mining pools control over 51% of the total hash power, the Nakamoto Coefficient would be 3, reflecting a low level of decentralization.

In the following sections, we’ll examine the Nakamoto Coefficient’s definition, calculation, key factors influencing it, and impact on blockchain security and fairness.

What is the Nakamoto Coefficient and Why Does it Matter?

Definition and Origins of the Nakamoto Coefficient

Decentralization in blockchain is not an absolute state, but rather a spectrum of implementation. To quantify this characteristic, the Nakamoto Coefficient was introduced. It is a key metric used to assess how decentralized a blockchain truly is. The concept was proposed by Balaji Srinivasan (former CTO of Coinbase) and Leland Lee, and is named after Satoshi Nakamoto, the creator of Bitcoin.

The Nakamoto Coefficient represents the minimum number of independent entities required to disrupt or control a blockchain’s most critical components, such as:

• Mining pools in Proof of Work (PoW) chains
• Validators in Proof of Stake (PoS) chains
• Node operators
• Governance participants (e.g., DAO members or token holders)

In other words, the Nakamoto Coefficient answers the question: How many independent participants must collude to compromise the blockchain? The higher the number, the more decentralized and secure the network. A lower number indicates power is concentrated, making the network more vulnerable to manipulation or attacks.

Nakamoto Coefficient vs. 51% Attack

While the Nakamoto Coefficient is conceptually similar to the 51% attack, it is broader in scope.

A 51% attack applies primarily to PoW blockchains. If one entity controls more than 50% of the hash rate, they can unilaterally validate transactions, perform double-spending, or reorganize the blockchain history.

In contrast, the Nakamoto Coefficient considers not only hashing power, but also node control, governance influence, staking weight, and other factors. It is applicable to PoW, PoS, and Delegated PoS (DPoS) blockchains alike.

For example, in a typical PoS network, if a small group of validators controls more than 33.33% of the staked tokens, they can block consensus formation, preventing new blocks from being added and possibly influencing governance decisions. If the Nakamoto Coefficient of a blockchain is 10, this means that at least 10 independent validators would need to coordinate to compromise the system. A low coefficient implies centralization and increased systemic risk.

Why is the Nakamoto Coefficient Important?

Decentralization is one of blockchain’s foundational values. It enables stronger security, greater censorship resistance, and reduced reliance on trust. However, if a small group of actors can easily control the network, several risks emerge:

• Reduced Security
  When the Nakamoto Coefficient is low, a few mining pools or validators may coordinate attacks like 51% attacks or intentionally delay transaction confirmations.

• Weakened Censorship Resistance
  If a handful of nodes control transaction validation, they can selectively block transactions, undermining openness and neutrality.

• Single Point of Failure (SPOF)
  If power is concentrated among a few entities, any compromise—such as hacking, regulatory action, or technical failure—could halt the entire network.

• Unfair Governance
  If governance is dominated by a small number of validators or token holders, they may steer protocol changes to serve their own interests rather than the community’s.
  These risks highlight that measuring decentralization isn’t just a theoretical exercise—it’s essential to ensuring that blockchain systems are fair, secure, and sustainable.

The Nakamoto Coefficient is Not the Only Decentralization Metric

While a high Nakamoto Coefficient implies a more distributed control structure, it does not guarantee full decentralization. Several other factors must be considered when evaluating the decentralization level of a blockchain:

• Geographical Concentration
  If most miners, validators, or node operators are located in a single country or region, even a high Nakamoto Coefficient may not safeguard the network from regional regulation, infrastructure failures, or political interference.
  For instance, many Ethereum validators are based in the U.S. If U.S. regulators impose stricter rules on PoS validators, it could affect the network’s operation.

• Infrastructure Centralization
  If most nodes run on a few cloud providers (e.g., AWS, Google Cloud), the network remains vulnerable to infrastructure-level SPOFs, even if control is widely distributed.
  For example, an AWS outage could take a significant portion of blockchain nodes offline, disrupting the network.

• External Influences
  Decentralization is not solely technical—it is also affected by regulation, government intervention, and corporate influence.
  Although a blockchain may appear decentralized technically, if its core developers or major token holders are subject to regulatory or corporate pressures, decision-making independence can be compromised.
  For instance, USDT (Tether) operates on blockchain networks but is centrally managed by the Tether company, making it more susceptible to regulatory actions.

These considerations show that decentralization is multi-dimensional, and the Nakamoto Coefficient only measures part of the picture. To fully assess a blockchain’s decentralization, one must also examine node distribution, infrastructure reliance, and external governance influences.

Risks of a Low Nakamoto Coefficient

When the Nakamoto Coefficient is too low, a blockchain becomes vulnerable to centralized control, resulting in several potential risks:

• 51% Attack (in PoW Chains)
  If a small number of mining pools control more than half of the network’s hash rate, they can manipulate transaction validation, execute double-spending attacks, and even reorganize blockchain history.

• Governance Manipulation (in PoS Chains)
  In Proof-of-Stake networks, if a small group of validators or token holders controls more than 50% of voting power, they can dominate protocol changes and implement rules that benefit themselves.

• Reduced Trustlessness
  One of blockchain’s core advantages is eliminating the need to trust a single authority. However, if control is overly concentrated, users are forced to rely on a few entities rather than the integrity of the network as a whole.

• Weakened Censorship Resistance
  When a small number of validators have the power to confirm transactions, they may choose to censor specific transactions, undermining financial freedom and network neutrality.

These risks highlight the critical importance of the Nakamoto Coefficient. Designing a fair consensus mechanism is not enough to ensure a blockchain remains sufficiently decentralized. The network’s actual operational decentralization must also be quantified through the Nakamoto Coefficient, with ongoing monitoring and optimization based on real-world data.

How is the Nakamoto Coefficient Calculated?

The calculation of the Nakamoto Coefficient depends on identifying the blockchain system’s most critical influence factors. Different consensus mechanisms (such as PoW and PoS) require different measurement approaches. The overall process can be broken down into the following steps:

1. Choose the Appropriate Measurement Dimension

The consensus mechanism used by a blockchain determines how power is distributed, which directly affects the Nakamoto Coefficient:

• Proof of Work (PoW): Measures the concentration of hash power across mining pools to ensure that no small group can dominate block production.
• Proof of Stake (PoS): Assesses the staking weight held by validators to evaluate their influence on consensus, ensuring fairness and security.
• Delegated Proof of Stake (DPoS): In blockchains like EOS or Solana that adopt DPoS, the number of validators is often fixed. This structural limitation means the Nakamoto Coefficient tends to be lower compared to PoW or PoS systems.

Different components of a blockchain may have varying levels of decentralization, so it’s important to focus on the core area being assessed. Common measurement dimensions include:

• Node Operators: Evaluate the minimum number of nodes required to maintain block synchronization and network stability.
• Governance Mechanisms: Determine the smallest number of voting rights sufficient to sway governance outcomes and prevent decision-making monopolies.
• Development Contributions: Analyze the influence of core development teams on the codebase to ensure that blockchain upgrades are not dependent on a single organization.

2. Calculate the Concentration of Influence

Once the appropriate dimension is selected, the next step is to assess the degree of influence concentration:

• Rank Entities by Influence:
  For PoW, rank mining pools by hash rate; for PoS, rank validators by staking weight.

• Aggregate Influence Until a Critical Threshold Is Reached:

  • PoW Chains: Calculate the number of the top mining pools needed to exceed 51% of total hash power.
  • PoS Chains: Determine how many top validators collectively control over 33.33% of staking power (enough to block consensus).
  • Governance: Measure how many top token holders can control the outcome of governance proposals.

3. Determine the Nakamoto Coefficient Value

Once the aggregated influence reaches the critical threshold, the minimum number of independent entities required is the Nakamoto Coefficient (N).

Examples:

• If just 3 mining pools control over 51% of Bitcoin’s hash rate, then Nakamoto Coefficient = 3.
• If 5 validators hold enough staked tokens to surpass 33.33% in a PoS system, then Nakamoto Coefficient = 5.
• If the top 7 token holders in a DAO can unilaterally pass proposals, then Nakamoto Coefficient = 7.

The higher the number, the more evenly distributed the influence, and the greater the degree of decentralization. Conversely, a low Nakamoto Coefficient suggests that control is overly concentrated, increasing the risk of manipulation and reducing network security.

Nakaflow: A Visualization Tool for the Nakamoto Coefficient

Nakaflow is a website that visualizes the Nakamoto Coefficient across major Proof-of-Stake (PoS) blockchains. The platform calculates these coefficients using publicly available data on token staking distribution—such as validator operators like Chainflow and staking pools like Lido.

Figure: Nakamoto Coefficient data displayed on the Nakaflow website
(Source: https://nakaflow.io/)

This tool provides valuable insight into the decentralization differences across various blockchain networks. For instance, Polkadot exhibits a relatively high Nakamoto Coefficient, indicating a broader and more balanced distribution among its validators. This is partly due to its use of Nominated Proof of Stake (NPoS), which promotes validator diversity.

On the other hand, Aptos has a comparatively lower Nakamoto Coefficient, suggesting a more concentrated validator set. However, it still ranks significantly higher than some traditional blockchains, demonstrating a stronger degree of decentralization.

Key Factors Influencing the Nakamoto Coefficient

The Nakamoto Coefficient reflects the level of decentralization within a blockchain system. Its value is influenced by several core factors, including the consensus mechanism, economic incentives, and network security. Beyond the consensus model (already discussed earlier), the following factors also significantly impact the Nakamoto Coefficient:

1. Economic Incentives

The economic design of a blockchain system directly affects the distribution of validators, which in turn influences the Nakamoto Coefficient:

• If the majority of validators or miners belong to a small number of large institutions, decision-making power becomes concentrated, resulting in a lower Nakamoto Coefficient and reduced decentralization.
• If the system is designed to offer sufficient financial incentives to attract a wide range of independent participants and support sustainable node operations, validator distribution becomes more diverse, increasing the Nakamoto Coefficient.

2. Network Security and Attack Risks

The security of a blockchain is closely tied to its level of decentralization. The following security-related factors may influence the Nakamoto Coefficient:

• 51% Attack Risk:
  When the Nakamoto Coefficient is too low, attackers only need to gain control over a few critical nodes to disrupt the network. This increases the risk of malicious manipulation and compromises blockchain integrity.

• Node Operation Barriers:
  If the technical or financial threshold for running a node is too high, fewer participants can join the consensus process. This narrows the pool of validators or miners, reducing decentralization and lowering the Nakamoto Coefficient.

Applications of the Nakamoto Coefficient

The Nakamoto Coefficient serves as a crucial metric for evaluating the level of decentralization in blockchain systems and has practical applications across various domains:

Blockchain Security Assessment

The Nakamoto Coefficient can be used to assess a blockchain network’s resistance to attacks. A low coefficient indicates that only a few entities are needed to control critical decisions, making the blockchain more susceptible to 51% attacks or oligopolistic control.

When designing or selecting a blockchain, analyzing the Nakamoto Coefficient helps determine its level of decentralization and inherent security. For example, in 2019, Ethereum Classic (ETC) suffered a 51% attack due to its low Nakamoto Coefficient, which led to millions of dollars’ worth of transactions being reorganized—clearly demonstrating the risk posed by low decentralization.

Governance Design and Optimization

In PoS and DPoS systems, decision-making power often hinges on validator stake weights or election methods. By monitoring the Nakamoto Coefficient, development teams and communities can identify centralization trends and adjust staking rules, voting mechanisms, or economic incentives to better distribute governance power.

Comparing and Choosing Between Public Chains and Sidechains

Developers and investors can use the Nakamoto Coefficient to compare decentralization across different blockchains and sidechains. In fields like DeFi, NFTs, and GameFi, a higher Nakamoto Coefficient suggests that the platform is less likely to be controlled by a single entity—providing a safer and more transparent environment for users.

Regulatory and Compliance Evaluation

As regulatory frameworks for blockchain continue to evolve, authorities can use the Nakamoto Coefficient to assess whether a blockchain is overly centralized and whether it meets decentralization standards.

For instance, a blockchain with a very low Nakamoto Coefficient might resemble a traditional centralized system and be subject to stricter regulations. The U.S. SEC once sued Ripple (XRP), arguing that the network was highly centralized because Ripple Labs held a large share of XRP tokens and exerted significant control over the network. If the XRP network had a higher Nakamoto Coefficient with a broader validator distribution, the SEC might not have classified it as being under the control of a single entity—potentially reducing compliance risk.

Supporting Decentralization Development

Communities and developers can monitor decentralization trends by tracking changes in the Nakamoto Coefficient over time. They can then improve decentralization by adjusting consensus mechanisms, lowering the barrier to node participation, or distributing staking rights more broadly, helping to ensure the blockchain evolves in alignment with long-term decentralization goals.

Figure: Community discussion on X speculating whether Cardano will become the first cryptocurrency to reach a Nakamoto Coefficient over 100
(Source: https://x.com/adahandle/status/1900247129144385897/photo/2)

Conclusion

The Nakamoto Coefficient is a vital metric for measuring decentralization in blockchain networks. It allows us to evaluate key attributes such as security, censorship resistance, and fairness in governance. A higher coefficient indicates a more widely distributed control structure, signifying stronger decentralization. Conversely, a lower value implies concentrated control, making the blockchain more susceptible to manipulation and attack.

However, the Nakamoto Coefficient is not the only standard for assessing decentralization. Factors such as geographic concentration, infrastructure dependency, and external influences are equally critical. Therefore, when evaluating a blockchain’s level of decentralization, one should adopt a holistic view rather than relying solely on a single metric.

Looking ahead, raising the Nakamoto Coefficient will depend increasingly on technological innovation and governance design. For instance, Polkadot’s Nominated Proof of Stake (NPoS) mechanism helps decentralize stake distribution by allowing nominators to delegate to multiple validators, reducing the risk of power concentration. Ethereum’s sharding mechanism also aims to scale validator participation and enhance network diversity. Beyond these, encouraging home staking and lowering node operation barriers can attract more independent participants and reduce reliance on large staking service providers. Other examples include Avalanche’s Subnet architecture and Cosmos’s modular multi-chain design, which both offer greater flexibility by decentralizing governance and validator control. These examples demonstrate that improvements in consensus mechanisms, node design, infrastructure distribution, and governance frameworks are all practical paths toward increasing the Nakamoto Coefficient and strengthening decentralization.

As these technologies and structures mature and see wider adoption, we move closer to building a truly censorship-resistant, manipulation-proof, and sustainable blockchain ecosystem—realizing the original spirit and vision of decentralization.

Figure: Ethereum’s Sharding Mechanism
(Source: https://www.gate.io/zh-tw/learn/articles/what-is-sharding/64)