Aptos’ validator footprint has narrowed sharply over the past two years, with fewer nodes, fewer countries, and a much heavier concentration in Europe and the Americas.
The article, written by r2Jamong and translated by AididiaoJP for Foresight News, says the change was not simply a matter of validators shutting down. It describes a broader reshuffling driven by faster chain performance, lower staking rewards, and a steep decline in the token’s dollar price, all of which changed where operators could keep running economically.
In October 2024, Aptos had 146 validator nodes spread across 22 countries and 48 cities. Beyond Europe and the Americas, the network still had nodes in Singapore, Tokyo, Seoul, and Hong Kong, as well as Sao Paulo in South America, Johannesburg in Africa, and Sydney in Australia. At that point, the network still looked broadly global.
By September 2026, that map had become much smaller. Validator count had fallen to 84, down 42%. Country coverage dropped to 13 and city coverage to 28, largely in step with the node decline. Most remaining validators were concentrated in Europe and the Americas. Outside those regions, only one node remained in Tokyo, while Aptos’ earlier multi-city presence in Asia had largely disappeared.
Faster chain performance made latency and location matter more
The report points to two developments happening at the same time. Aptos became faster, making it harder for remote validators to operate steadily, while lower rewards and a falling token price put pressure on validator finances.
In June 2025, the Baby Raptr upgrade and AIP-131, or Velociraptr, pushed Aptos block times to below 50 milliseconds. That was a clear improvement for users and trading activity. For validators, though, network conditions and data center location stopped being secondary considerations.
Aptos calculates rewards using staked amount, reward rate, and validator proposal success rate. The farther a node is from the main validator cluster, the more likely its proposal success rate is to fall even with the same amount staked. That directly cuts revenue. Validators spread across different continents were therefore hit first by the economics of the system, making shutdowns or relocation to Europe and the Americas a more rational choice.
The article also says higher performance raised hardware requirements. At the same time, memory prices were pushed up by AI demand, adding to fixed validator costs. Operators that were far away, small in scale, and already working with thin margins were the first to struggle.
That creates a broader tension for proof-of-stake networks. Faster consensus can end up compressing geographic diversity. Latency is a physical constraint, and when rewards are tied to proposal success, nodes naturally move toward lower-latency regions. Under that setup, decentralization in geographic terms can narrow as performance targets rise.
Revenue pressure became the direct reason validators left
The piece says validator exits were still decided most directly by income. Validators earn in tokens, but they pay for data centers, bandwidth, operations, and labor in dollars. Those revenue and cost lines do not move in the same market cycle.
Aptos annualized staking rewards fell from 7% in October 2024 to 2.6% in September 2026, a 63% decline. The path was laid out in stages. AIP-119, proposed in April 2025, reduced the rate from 7% to 5.19% starting in June that year. Then a tokenomics adjustment proposed by the foundation in February 2026 lowered it again to 2.6%.
Because validator income comes from a commission share of delegated staking rewards, lower reward rates reduced earnings for both delegators and operators at the same time.
The deeper break in validator economics came from price. Over the same period, APT fell from $9.50 to $0.58, a 94% drop. After weaker validators left, average stake per node rose from 5.75 million APT to 8.97 million APT, up 56%. Staking became more concentrated, but the increase in stake per validator was nowhere near enough to offset the combined impact of lower reward rates and the token’s price collapse. Measured in dollars, annualized rewards fell 96%.
The article frames the math plainly: a 56% increase in stake could not make up for a 96% collapse in revenue. That, it says, is the arithmetic foundation of the validator exit wave.
It adds that a shift toward lower issuance and lower staking rewards may make sense from the standpoint of long-term dilution, but it comes with a cost. Validator businesses become thinner, and network distribution narrows with them. Tightening issuance while keeping operators financially healthy is hard to do at the same time.
The same pressure exists on other PoS chains
The report argues that Aptos is not unique. Many proof-of-stake networks share the same structure: income arrives in tokens while costs are paid in fiat. When the market weakens, smaller operators and those in peripheral regions tend to leave first. What remains more often are exchanges, institutions, and professional validators already operating in European or American data center hubs.
It points to a similar debate in the Ethereum community. EIP-8363 proposes burning part of newly issued staking rewards when the staked amount expands, in an effort to curb inflation and excessive staking growth. The article says that direction resembles Aptos’ reward cuts, but it also requires a careful look at how much validator economics can bear.
In that framing, decentralization cannot be measured only by validator count and staking ratio. A more important question is whether a sufficiently diverse group of operators can stay in the network when token prices fall and reward policies change. Validator numbers can expand in a bull market and then be reordered by cost in a weaker cycle.
The article says operators that can absorb short-term reward volatility become more important in this phase. Exchanges and institutions have other business lines, long-term service needs, and greater capacity to remain active through downturns. For that reason, exchange staking and institutional-grade validators can contribute positively to network stability. But a rising share of those participants can also weaken both geographic diversity and diversity of operator types. Stability and dispersion do not always move in the same direction.
Long-term decentralization depends on costs and open entry
Another point in the article is the importance of entry barriers. Most public blockchain engineering work is focused on raising performance and throughput. The piece argues that efficiency should get equal attention: achieving similar performance with less hardware, lower power costs, and lower bandwidth demands.
If that barrier comes down, new operators have a better chance to join, and existing ones have more room to survive under lower rewards. Otherwise, a “globally distributed” network may remain true only on paper, while actual validator infrastructure contracts toward a small number of cloud regions.
The article says Aptos’ changes over the past two years do not simply prove that decentralization has failed. Instead, they reveal a set of constraints:
- Performance upgrades change who is suited to be a validator.
- Rewards and token prices determine who can still afford to keep nodes running.
- The operators that remain will shape the network map in the next phase.
In the end, the report says long-term decentralization depends on three things: validators that can keep running through weak markets, operating costs that can be pushed down effectively, and an environment that remains open to new entrants. If any one of those is missing, validator numbers may still look acceptable for a while, but geographic distribution is likely to narrow first.