In 1994, mathematician Peter Shor showed that a quantum computer could factor large numbers fast enough to break the encryption used to secure most of the internet. Thirty-two years later, no one has built a machine capable of doing that.
But the framing that has defined quantum computing for most of those decades — that practical machines are perpetually "a decade away" — is dissolving, not because the hard physics got easier, but because the technology is starting to show up in places where it can be measured against real infrastructure rather than distant promises.
The decade that never ended
Shor's algorithm is a quantum algorithm for factoring integers, developed by Peter Shor in 1994. It was a powerful motivator for the design and construction of quantum computers, and for the study of new quantum-computer algorithms. The problem was that building such a machine required thousands, perhaps millions, of qubits operating with error rates that no one knew how to achieve. The "decade away" framing became self-reinforcing.
A National Academies of Sciences, Engineering, and Medicine report noted that quantum computing appeared on Gartner's list of emerging technologies 11 times between 2000 and 2017, each time at the earliest stage of the hype cycle and categorized as more than 10 years from commercialization. When the National Academies published its own assessment in 2018, the conclusions were consistent: "Significant technical and financial issues remain towards building a large, fault-tolerant quantum computer, and one is unlikely to be built within the coming decade." That same year, Boston Consulting Group published its own analysis, concluding that "the full impact of quantum computing is probably more than a decade away," though it noted a closer disruption was gathering force in the near term.
The pattern was not dishonest. The problems were real. Qubits are fragile. Noise accumulates. Error correction demands enormous overhead. Each time a milestone was hit, the remaining distance to a useful machine stayed long.
3 milestones that shifted the conversation
In October 2019, Google $GOOGL published results in Nature showing that its Sycamore processor completed a task in about 200 seconds that the company estimated would take a classical supercomputer about 10,000 years. Google called it quantum supremacy. IBM $IBM countered that Google's claim was overstated, and the clash highlighted the intense commercial interest in the field. Whether the benchmark qualified as true supremacy was debated, but the result demonstrated a new level of control over 53 qubits operating together.
Five years later, in December 2024, Google announced Willow, a 105-qubit chip that could reduce errors exponentially as it scaled up, cracking a challenge in quantum error correction that the field had pursued for almost 30 years. Willow also performed a benchmark computation in under five minutes that would take a supercomputer 10 septillion years. The error correction result mattered more than the benchmark. Operating "below the threshold" had been a goal for error-corrected quantum computing since the 1990s, and after almost 30 years of advancement, quantum computers still had not passed this landmark — until Willow.
Then in February 2025, Microsoft $MSFT introduced Majorana 1, a quantum chip powered by a new Topological Core architecture that it said would realize quantum computers capable of solving industrial-scale problems in years, not decades. The company placed eight topological qubits on a chip designed to scale to one million. Members of the quantum community questioned the claim, and some experts debated its experimental validity and interpretation, given Microsoft's 2018 retraction of a related claim about Majorana zero modes. But the design itself mattered for a different reason: the chip, with both qubits and control electronics, fits in the palm of a hand and can be deployed in a quantum computer running inside Azure data centers.
From the lab to the rack
Each of these milestones was reported in isolation, as a physics result. What changed is where the technology started going afterward. On May 4, 2016, IBM put the first quantum computer on the cloud, a five-qubit processor available to anyone with an internet connection. That decision created a developer community.
A decade later, the IBM cloud hosts 240,000 users and supports a network of 300 ecosystem partners. IBM's roadmap now extends through the early 2030s. The company plans to deliver its first fault-tolerant quantum computer, called Starling, in 2029, with 200 qubits running 100 million gates. By 2033, it envisions a 2,000-qubit system called Blue Jay, capable of running one billion gates.
At its November 2025 Quantum Developer Conference, IBM unveiled progress toward delivering quantum advantage by the end of 2026 and fault-tolerant quantum computing by 2029. The IBM-RIKEN collaboration made the integration concrete. IBM and RIKEN unveiled the first IBM Quantum System Two deployed outside the U.S., and it was co-located with RIKEN's Fugaku supercomputer, one of the most powerful classical systems on Earth. The two machines ran a quantum chemistry problem in a closed loop, feeding data back and forth in an unbroken workflow.
That is not a demonstration of physics. It is a demonstration of computing architecture. NVIDIA, meanwhile, announced Ising, a family of open-source quantum AI models that span key quantum workloads, starting with calibration for automating the tuning of quantum processors and decoding for accelerating real-time quantum error correction. The premise is that GPUs should manage the classical bottlenecks, such as error correction and calibration, that limit quantum hardware. The models integrate with NVIDIA's CUDA-Q software platform and the NVQLink hardware interconnect to connect quantum processors to GPU systems.
What broke the framing
The "decade away" framing held because quantum computing remained a physics experiment. Progress was measured in qubit counts and gate fidelities, metrics legible to researchers but opaque to anyone planning infrastructure budgets. What disrupted it was not a single result but a convergence.
Microsoft designed a quantum processor to fit into standard server rack footprints. IBM put a quantum computer next to a classical supercomputer and ran real workloads between them. NVIDIA built AI models to enable quantum hardware to function reliably enough for deployment. These are not milestones in physics. They are milestones in engineering and integration.
In 2020, McKinsey estimated that 5,000 quantum computers would be operational by 2030, though the hardware and software needed to handle the most complex problems may not be available until 2035 or later. That sounds like the same old timeline. The difference is that the machines showing up in 2026 are not laboratory prototypes awaiting a physics discovery. They are processors connected to the existing computing infrastructure, sitting in data centers next to the CPUs and GPUs that run everything else.
The decade may still be about right. But for the first time, what it measures is an engineering schedule, not a physics hope.