Quantum computing is about to enter an important stage: the era of quantum advantage. In this era, a quantum computer will be able to run certain computations more accurately, cheaply, or efficiently than a classical computer. Between now and the end of 2026, IBM predicts that the quantum community will have uncovered the first quantum advantages for industry. Currently, IBM is driving toward building a large‑scale, fault-tolerant quantum computer by 2029.
IBM has long stated that we will not achieve quantum advantage alone. We work closely with partners to discover algorithms and applications in their areas of expertise, like chemistry, finance, and pharmaceuticals. National Taiwan University is one of those important partners pursuing quantum computing today. Enterprises that adopt this technology today, and participate in the search for quantum advantages now, stand to benefit the most as the technology matures.
There won’t be one eureka moment where an all-encompassing quantum advantage conclusively appears. Different advantage claims will emerge in different fields at different times. The first claims of quantum advantage are already emerging today, though none have been validated. We expect researchers and developers to present further compelling hypotheses for quantum advantages over the next couple of years. In each case, the broader community will examine the work and either disprove these hypotheses with cutting-edge techniques—or the advantage will hold.
What makes us so confident? Well, we have already arrived at a place where quantum computing is a useful scientific tool capable of performing computations that exact classical simulations of quantum computers can’t. In our work with RIKEN in Japan and Cleveland Clinic in the US, we have performed computations potentially useful for drug discovery that have the potential to outperform what classical approximation methods could do alone.
We and our partners are already conducting a range of experiments on quantum computers that are designed to extend beyond the capabilities of classical methods alone. At the same time, the community of computing researchers are testing advantage claims with innovative new classical approaches.
Before the end of the decade, we aim to implement fully realized fault-tolerant quantum computing. Doing so will require quantum error correction to unlock new potential applications. Our roadmap charts our course toward this milestone and promises the realization of IBM Quantum Starling, a quantum computer capable of running 100 million gates on 200 logical qubits by 2029—that’s more power than the combined memory of billions of billions of classical supercomputers. This year, we released a plan demonstrating all of the steps required to build this system, incorporating the latest in quantum error correction codes, decoding, and realizing modularity with quantum interconnects.
The advantages we discover today are the applications that will bring business value, and the ones that we will scale to Starling in 2029. Today, a new set of techniques have arisen that can reduce and eliminate bias in expectation value calculations caused by noise in quantum circuits. We call these error mitigation techniques: They “mitigate” the effects of noise. Error mitigation is crucial for achieving quantum advantage in 2026, and is likely to play an important role in early fault‑tolerant regimes.
A number of our partners are building powerful error mitigation methods, which can be accessed as services in our Qiskit Functions Catalog. These methods enable users to use today’s best quantum computers more effectively, stretching their capabilities into the realm of advantage. Thanks in large part to those efforts, our users are drafting and beginning to present hypotheses of advantage to the community.
In May, researchers at the startup Kipu Quantum claimed a runtime quantum advantage, where their quantum algorithm ran faster than specific-purpose classical solvers for dense, higher-order unconstrained binary (HUBO) optimization problems. They expect their runtimes to be soon be orders of magnitude faster as hardware continues to advance.
Startup Q‑CTRL has also benchmarked IBM Quantum systems against classical, quantum annealing, and trapped‑ion technologies for optimization, unlocking a more than 4x increase in solvable problem size and outperforming commonly used classical local solvers. In a recent collaboration with Network Rail on a scheduling solution, Q‑CTRL made the largest demonstration to date of constrained quantum optimization, accelerating the path to practical quantum advantage.
Meanwhile, one family of “variational” algorithms combine quantum and classical computing resources to return solutions with comparable accuracy to the leading classical approximation methods for chemistry and materials science. Thanks to the variational principle, quantum advantage appears close in the fields of chemistry and materials science.
Last month, RIKEN and IBM demonstrated the use of one such technique to simulate molecular nitrogen and two species of iron‑sulfur clusters, 2Fe‑S and 4Fe‑2S. Their experiments used up to 77 qubits of the IBM Quantum Heron processor running up to 3,500 two‑qubit gate operations alongside the Fugaku supercomputer to simulate the molecules. These quantum-centric computations went beyond the limit of exact classical stimulation, and suggest potential advantage as the quantum-high performance computing integration improves.
In a paper published in Nature Communications, IBM and University of Tokyo researchers demonstrated impressive results for an approach suited to materials science applications.
This is a marathon, not a sprint. While IBM continues to release more performant quantum computers, it is essential that the quantum community keeps developing new algorithms, all in the name of creating the applications that will bring useful quantum computers to the world.
There’s never been a better time to get started using quantum computing.
