IBM’s Nighthawk r2 quantum processor generated one million samples from a specialized random-circuit benchmark in 19 seconds, according to a September 2026 preprint. The paper’s authors estimate that a specified classical simulation approach would take more than a century on the Frontier supercomputer to produce a comparable sample set under their assumptions. That is a narrow benchmark comparison—not evidence that quantum computers now perform ordinary computing tasks 110 years faster.
What did IBM’s quantum computer do in 19 seconds?
The experiment used IBM’s 120-physical-qubit Nighthawk r2 superconducting processor, identified in the paper as ibm_phoenix. Researchers ran a 61-qubit random quantum circuit and collected 1,000,000 output bit strings for a circuit with 36 cycles. The paper reports that sample collection took 19 seconds. The result and its technical details are described in the authors’ September 2026 arXiv preprint.
Random-circuit sampling means executing a selected random quantum circuit and recording bit-string outputs drawn from its output distribution. The task tests a processor’s ability to run circuits and sample their outputs; it is not a calculation of a practical answer such as a new drug, a delivery route, or an investment decision.
How was the “more than 100 years” comparison calculated?
The century figure is the preprint authors’ modeled estimate, not the result of timing a complete, equivalent run on Frontier. At the reported linear cross-entropy benchmarking fidelity of 2.3 × 10-3 for the 36-cycle circuit, their bounded-fidelity rejection-sampling model implies 1.2 × 1027 machine operations to generate a comparable one-million-sample ensemble. They characterize that workload as taking more than a century on Frontier, assuming favorable memory availability.
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Those qualifications matter: the estimate depends on the chosen classical algorithm, target fidelity, sample count, and memory assumptions. It is not a universal lower bound on classical computing time. Different simulation methods or improved algorithms could change the comparison.
How did the authors check the quantum result?
The researchers report agreement across measured circuit depths between two independent fidelity-estimation methods: mirror benchmarking and cross-entropy benchmarking. The 36-cycle comparison uses the paper’s stated linear cross-entropy benchmarking fidelity. The authors describe their work as, to their knowledge, the first demonstration of quantum advantage for “vanilla” random-circuit sampling on a commercially and broadly accessible processor that non-experts can replicate. That is the authors’ characterization of this benchmark, rather than an independent field-wide judgment.
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Does this mean quantum computers are better than supercomputers?
No broad conclusion follows from this one workload. The result indicates an advantage for a specific random-circuit-sampling task under a particular comparison model; it does not show that a quantum processor is faster, cheaper, or more accurate for general-purpose computing or for a useful commercial application.
IBM’s own framework says a quantum-advantage claim should involve an output that can be rigorously validated and a task with superior efficiency, cost-effectiveness, or accuracy compared with classical computation. IBM also describes advantage as potentially involving quantum processors augmenting classical workflows. That is IBM’s stated framework, not a universal definition accepted by every organization. See IBM’s explanation of quantum advantage.
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Is the paper peer-reviewed?
The cited work was submitted to arXiv on 23 September 2026, and the version described here is version 1. The available record establishes a preprint submission, not publication in a peer-reviewed journal. The finding should therefore be attributed to the paper’s authors, and its runtime comparison treated as their model-based estimate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How is this different from IBM’s other quantum results?
IBM has described other demonstrations that involve different tasks and should not be ranked as direct speed comparisons with Nighthawk’s random-circuit benchmark.
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| Demonstration | Workload and hardware | What the reported result concerns |
|---|---|---|
| Nighthawk r2, 2026 | Random-circuit sampling; 61 of 120 physical qubits | One million samples collected in 19 seconds; the classical century-scale figure is a modeled estimate from the preprint authors. |
| Eagle, 2023 | Material-system spin dynamics; IBM’s 127-qubit processor | A separate error-mitigated modeling experiment compared with classical simulations. IBM described it as a step toward modeling a physical system beyond leading classical approaches. IBM’s 2023 announcement. |
| IBM and University of Chicago, 2026 | Logical circuits; 70 logical qubits | A separate logical-circuit demonstration reporting approximately 15 minutes of quantum computation. IBM’s July 2026 announcement. |
These experiments differ in workload, physical versus logical qubits, validation, and classical comparison. Their figures cannot be combined into a single speed ranking.
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