The Nakamoto Coefficient is the smallest number of independent entities that would need to collude to compromise a blockchain’s consensus. In Proof-of-Work, that means mining pools with enough combined hashrate to rewrite the chain. In Proof-of-Stake, it means validator operators with enough combined stake to stall it. A higher number means more parties have to agree before anything breaks. A lower number means fewer.
Here is why that number is worth more than any figure in a pitch deck. Ethereum has roughly 1,278,000 validators. Chainspect lists its Nakamoto Coefficient at 1.
That gap between the headline figure and the effective one is what the metric exists to expose.
Where Did the Number Come From?
Balaji Srinivasan and Leland Lee published “Quantifying Decentralization” in July 2017. Their complaint was straightforward: decentralization was the main selling point of Bitcoin and Ethereum, and almost nobody was measuring it.
They borrowed the framing from economics. The Lorenz curve plots how unevenly wealth spreads across a population. The Gini coefficient squeezes that curve into a single number between 0 and 1. Srinivasan and Lee applied the same thinking to blockchains, then added a step: break the system into its essential subsystems, work out the minimum number of entities needed to control each one, and take the lowest result across all of them.
That lowest result is the minimum Nakamoto Coefficient. The subsystems they listed covered mining or staking, client software, developers, node operators, exchanges, and token ownership. In practice, nearly every dashboard reports only the consensus layer, because it is the one that can be measured cleanly and the one that fails fastest.
The name is a nod to Satoshi Nakamoto, and to the property Bitcoin was built to have in the first place.
How Is It Calculated?
The method is simple. The data collection is the hard part.
- Identify the entities and their share of control, grouped by real-world operator rather than by individual node or validator key.
- Rank them from largest share to smallest.
- Add the shares cumulatively until you cross the critical threshold.
- Count how many entities you’d need. That count is the coefficient.
Thresholds depend on the consensus design:
- Proof-of-Work uses 51% of hashrate, the point at which a majority attack or chain reorganization becomes possible.
- Proof-of-Stake usually uses 33% of stake, enough to stall finality in BFT-style systems. Some trackers use 50% instead.
Run it on Bitcoin with live pool data. Over the seven days to July 17, 2026, mempool.space put Foundry USA at 27.6% of hashrate, F2Pool at 17.8%, AntPool at 17.3%, ViaBTC at 9.5% and SpiderPool at 5.7%.
- Foundry plus F2Pool comes to 45.4%. Short of the line.
- Add AntPool and you reach 62.7%. Over it.
- Three pools. Coefficient of 3.
Chainspect reports the same figure. Bitcoin runs 145 mining pools and three of them decide the answer.
Where Do the Major Chains Stand?
A snapshot from Chainspect’s decentralization dashboard, taken July 17, 2026 at 12:52 UTC:
- Polkadot: 166 (@Polkadot)
- TON (network token now GRAM): 72 (@ton_blockchain)
- Avalanche: 25 (@avax)
- Sui: 19 (@SuiNetwork)
- Solana: 18 (@solana)
- Cardano: 15 (@Cardano)
- Aptos: 14 (@Aptos)
- ICP: 14 (@dfinity)
- TRON: 13 (@trondao)
- Algorand: 12 (@Algorand)
- Tezos: 12 (@tezos)
- MultiversX: 11 (@MultiversX)
- $NEAR: 9 (@NEARProtocol)
- Sei: 8 (@SeiNetwork)
- $BNB Chain: 7 (@BNBCHAIN)
- Hedera: 7 (@hedera)
- Polygon: 4 (@0xPolygon)
- Bitcoin: 3 (no single official central account)
- Stellar: 3 (@StellarOrg)
- Ethereum: 1 (@ethereum)
Read those against validator counts and the ranking rearranges itself. Polkadot posts a 166 from 600 validators. TRON posts a 13 from a validator set of just 27, meaning almost half its Super Representatives would have to move together. MultiversX runs 3,250 validators and scores 11. Cardano runs 2,088 and scores 15.
Ethereum has more validators than every other chain on that list combined and sits at 1, because Chainspect groups pooled and liquid staking providers under the operators actually holding the keys. Volume of validators is not distribution of control.
The rollups make the same point with less ambiguity. Arbitrum, Base, Optimism, Starknet and Etherlink each list a single validator and score 1. Their sequencers are centralized, which everyone in the space already knows and few dashboards bother to quantify.
Why Does It Matter?
- Attack resistance. It puts a number on how hard a 51% attack, a censorship campaign or a halted chain actually is to pull off.
- Trust minimization. Blockchains sell themselves on not needing trusted third parties. A coefficient of 1 or 2 means you are trusting third parties, whatever the marketing says.
- Risk assessment. Concentrated control raises the odds of collusion, regulatory capture and single points of failure.
- A design target. Projects use it to benchmark themselves and to justify staking caps, delegation limits and anti-concentration rules.
What It Does Not Tell You
The metric has real limits, and treating it as a security score is a mistake.
Entity identification is imperfect. Two validators run by the same company under different names count as two. Dozens of validators sitting in the same cloud region count as dozens. Neither is true in a crisis.
The number moves. Stake shifts, pools merge, protocols upgrade. A screenshot from six months ago tells you very little today.
And it only looks at one dimension. Client diversity, developer concentration, governance capture and geographic clustering all sit outside the calculation. A chain can post a strong coefficient and still be taken down by one client bug or one regulator.
How fast the ground moves is visible in the data itself. TON’s coefficient fell 13.25% inside a single day to 72, tracking a 13.27% drop in its validator count. And the scale of what sits behind a score is invisible from the score alone. Bitcoin and Fogo both post a 3. Bitcoin has 145 mining pools and 1.11K EH/s behind that number. Fogo has seven validators. Same score, nothing else in common.
Sources
- Quantifying Decentralization – The original July 2017 essay by Balaji S. Srinivasan and Leland Lee introducing the minimum Nakamoto Coefficient.
- Chainspect Decentralization Dashboard – Live Nakamoto Coefficient, validator and stake data across 50+ blockchains, updated continuously.
- Bitcoin Mining Pool Stats – Seven-day rolling pool hashrate distribution sourced from mempool.space block production data.
- Nakaflow – An alternative real-time Nakamoto Coefficient tracker run by Chainflow, useful for cross-checking entity grouping.
- What Is the Nakamoto Coefficient and How Is It Calculated? – ForkLog’s breakdown of the subsystem approach and its links to the Lorenz curve.
