What is this?

This chart shows the cumulative number of Kaspa addresses holding at least a given KAS balance threshold over time. Each line represents a tier — addresses with ≥0.01 KAS, ≥1 KAS, ≥100 KAS, ≥1,000 KAS, ≥10,000 KAS, ≥100,000 KAS, and ≥1,000,000 KAS. The cumulative nature means every address that qualifies for a higher tier is also counted in all lower tiers. This gives you a layered view of network participation from the smallest dust holders up to the largest whales.

Address distribution is one of the most important on-chain metrics for gauging real adoption. While market cap and price tell you about speculative interest, address growth reveals organic network usage. A healthy, decentralizing network shows steady growth across all tiers — not just at the top. Kaspa's rapid 1 BPS block rate and low transaction fees make it accessible for micro-transactions, which often manifests as growth in the lower balance tiers.

It's important to note that Kaspa uses a UTXO-based model (similar to Bitcoin), which means a single user can control multiple addresses. Exchanges, mining pools, and privacy-conscious users routinely split funds across many addresses. Therefore, address counts represent an upper bound on unique participants — the true number of individual holders is likely lower, but trends over time remain meaningful regardless.

How to use this data

Growth in lower thresholds (≥0.01, ≥1, ≥100 KAS) indicates retail adoption — new users entering the network, faucet distributions, or airdrop activity. This is the broadest measure of network participation and often leads price rallies as a growing user base creates organic demand. Compare retail growth rates to those of other Layer-1 chains at similar market cap stages to gauge relative adoption velocity.

Growth in upper thresholds (≥10K, ≥100K, ≥1M KAS) reveals whale accumulation. When large holders are increasing during price consolidation or decline, it often signals smart-money confidence in future appreciation — a classic accumulation phase. Conversely, declining whale addresses during price pumps may indicate distribution, where large holders sell into retail demand.

Watch for divergences: if the total address count grows but upper tiers decline, the network is becoming more decentralized — supply is spreading from few large holders to many smaller ones. If upper tiers grow while lower tiers stagnate, concentration is increasing, which may pose governance and liquidity risks.

How it's computed

The system scans Kaspa's complete UTXO set and aggregates all unspent outputs by their destination address. Each unique address receives a total balance equal to the sum of all its UTXOs. The address is then placed into every cumulative threshold bucket it qualifies for — an address with 5,000 KAS counts toward the ≥0.01, ≥1, ≥100, and ≥1,000 KAS tiers simultaneously.

This snapshot is taken at regular intervals and stored as a time-series dataset. Because the computation requires scanning the entire UTXO set (which grows over time as more transactions occur on the network), it is performed server-side and cached. The DAG structure means multiple blocks are confirmed in parallel, so UTXO set changes are frequent — our sampling interval balances accuracy with computational efficiency.

Note that addresses with zero balance (fully spent UTXOs) are not counted. Only addresses with at least one unspent output contribute to the distribution. Historical data points reflect the state of the UTXO set at the time of each snapshot, enabling trend analysis across weeks, months, and years.