Qubic qubic

Qubic is a decentralized, open-source Layer 1 network designed for high-throughput smart contracts, oracle data, and outsourced computation. Its official site describes instant finality and feeless transactions, while the project’s GitHub profile describes Qubic as a platform for smart contracts, oracles, and outsourced computations based on quorum consensus. The native asset is QUBIC.

The protocol’s distinctive objective is to connect blockchain infrastructure with decentralized artificial-intelligence research. Qubic’s Useful Proof of Work (UPoW) directs participating compute toward useful tasks, particularly artificial-neural-network work associated with Aigarth, Qubic’s decentralized-AI initiative, rather than only toward arbitrary hash puzzles.

Qubic is intended to be a performance-oriented network: the homepage reports a CertiK-verified peak of 15.52 million transactions per second and says smart-contract transfers can exceed 55 million per second. These are project-reported benchmark claims, not a guarantee of sustained production throughput for every workload. Qubic’s mainnet is identified by the project as live since April 2022.

The project says it had a fair launch with no premine or venture-capital money. Qubic was founded by Sergey Ivancheglo (Come-from-Beyond), whom the project credits with work on NXT and IOTA. The whitepaper is a versioned technical overview and explicitly notes that Qubic remains in active development.

Qubic targets several limitations that its whitepaper attributes to conventional Layer 1 systems: transaction fees, latency, limited throughput, and consensus designs that may consume substantial resources without producing useful computation. These limitations make high-frequency applications and large-scale computation more difficult to operate.

The project also frames centralized AI compute as a problem. Training advanced models generally requires concentrated resources, which can create control, access, transparency, and resilience concerns. Qubic’s proposed answer is to let a broad set of contributors provide CPU computation through UPoW and to use that output for Aigarth’s distributed AI work.

Qubic additionally addresses governance and fault tolerance through a quorum-based design with Byzantine-fault-tolerance principles. This is a protocol design goal rather than proof that all centralization, economic, software, or operational risks have been eliminated; the whitepaper’s disclaimer identifies the system as an active-development project and warns of technology, market, and regulatory risks.

Qubic’s consensus uses a fixed committee model described in the whitepaper as 676 Computors. A transaction or network state requires agreement from at least 451 Computors to form a quorum. The design is based on quorum consensus and Byzantine Fault Tolerance, with quorum intersection intended to preserve consistent decisions despite a bounded number of faulty or malicious participants. The project’s GitHub organization publishes the core node software that runs the Qubic Network.

Transactions are designed to be feeless and to reach finality quickly; the whitepaper describes sub-second finality, and the homepage describes instant finality. The system supports smart-contract execution, oracle connectivity, and outsourced computation. The homepage also says Qubic operates with dynamic assembly of Computors for decentralization, while implementation and operational details should be checked against the current documentation and core releases.

UPoW changes the purpose of mining by assigning contributors useful computational tasks. The whitepaper describes CPU-based participation and computation for training or validating artificial neural networks in Aigarth. A miner’s contribution is discussed in terms of processing iterations and valid solution submissions, with adaptive task difficulty intended to preserve relative ranking as tasks change. Qubic therefore presents mining as both network participation and a source of distributed AI computation.

QUBIC is used as the native economic unit for participation and ecosystem activity. The project describes deflationary mechanisms including burns associated with smart-contract operations and a Smart Contract IPO model, in which contracts launch through an IPO-style process. Exact supply, emissions, burn totals, and contract-specific economics can change; users should consult the current whitepaper, official documentation, and on-chain explorer rather than relying on historical marketing metrics.