Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare routes to this goal, using different qubit technologies and logical arch
Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare routes to this goal, using different qubit technologies and logical architectures. Tracking progress toward quantum utility therefore requires rigorous benchmarks that measure computational capability relative to utility-scale challenge problems and enable fair comparison across disparate platforms. Here we demonstrate direct, cross-platform measurement of quantum computational capability using a new benchmark that quantifies the size of the largest computationally relevant quantum circuits that a machine can execute successfully and the speed at which it can execute them. We apply this quantum universal operation performance system (QUOPS) experimentally to leading processors from Quantinuum, Google, and IBM, computing directly on physical qubits. Translating state-of-the-art resource requirements for recognized challenge problems that represent useful quantum computation into effective QUOPS circuit sizes shows that computational capability must grow by 5 orders of magnitude, motivating fault-tolerant approaches. We use the same benchmark to assess the performance of a simple fault-tolerant logical-qubit processor implemented on up to eight [[7,1,3]]-encoded logical qubits using Quantinuum Helios-1, and project the growth of capability across successive generations of fault-tolerant quantum computers to show how QUOPS can track progress toward quantum scientific utility.