Xelis (XEL) Taschenrechner

Xelis advances privacy-preserving blockchain design by combining a BlockDAG architecture with a hybrid consensus that layers mining validation and additional cryptographic verification, yielding parallel transaction processing, lower orphan rates, and shorter time to usable confirmations while sustaining robust security at roughly 15.8-second block intervals; its CPU- and GPU-friendly XelisHash v2 mining algorithm (often referred to as XELIS Hash) counters ASIC concentration and broadens participation, reinforcing decentralization at the network edge, while a moderate, predictable issuance policy balances security incentives with controlled inflation dynamics over time; on the data layer, an account-based model replaces traditional UTXO linkages to streamline state updates and reduce linkability, and core privacy is delivered via homomorphic encryption and advanced zero-knowledge proofs that encrypt balances and amounts by default yet permit selective disclosure, enabling users to prove compliance or solvency without revealing underlying data; this cryptographic posture underpins confidential smart contracts-executed via the project’s dedicated virtual machine, XVM-that support private logic, confidential assets, and application patterns such as privacy-preserving decentralized exchanges, secret-ballot voting, and secure identity verification workflows; operationally, the BlockDAG structure increases throughput under real-world latency by admitting concurrent blocks and reconciling them with deterministic rules, which reduces contention in peak periods and minimizes wasted work, while the hybrid verification layers strengthen integrity against reordering and double-spend attempts; taken together, Xelis integrates established primitives with purpose-built implementations to address the sector’s central trilemma of scalability, privacy, and decentralization, and its growing footprint reflects market recognition that selective transparency, efficient proof verification on commodity hardware, and developer-ready confidential execution are practical prerequisites for privacy-first financial and governance applications.