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IBM research chief Dario Gil was describing a possible future advantage on particular calculations—not claiming that quantum computers already outperform classical supercomputers across the board. His “million or a billion” comparison, made in a December 2023 CBS 60 Minutes segment, was a forward-looking statement, not a reported benchmark.
What did Dario Gil mean by “a million or a billion” supercomputers?
In a CBS 60 Minutes discussion of IBM’s quantum systems, Gil said: “But the beauty of it, is that we see that we’re gonna continue to expand that capability, such that not even a million or a billion of those supercomputers connected together could do the calculations of these future machines.” Gil is IBM’s senior vice president and director of research.
The key words are “these future machines” and “the calculations.” Gil was talking about a prospective quantum advantage on selected tasks as quantum hardware develops. He was not saying that a quantum computer can do every kind of computing faster, nor that IBM had already demonstrated a machine with the capability he described. The comparison is qualitative: the CBS segment does not present it as a measured result, and no independent benchmark establishing that million-or-billion comparison is identified in the cited coverage.
Why could a quantum computer have an advantage on some tasks?
A classical computer represents information with bits, processed through ordinary operations. A quantum processor uses qubits and quantum effects. For some carefully chosen problems, a quantum algorithm could exploit those effects to reach a result in a way that would be impractical for classical machines. That possibility is the basis of “quantum advantage.” It does not mean quantum hardware is a universally faster replacement for conventional computers.
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Whether an advantage is useful depends on the problem, the algorithm, and the machine’s reliability and scale. Adding qubits alone is not enough: the system must control them reliably, connect them in useful ways, and correct errors well enough to carry out longer computations. The Guardian’s 2023 coverage of IBM’s Heron processor described connecting chips and machines as part of the company’s approach, while treating larger fault-tolerant capability as a future objective.
Quantum computers and supercomputers are suited to different work
| Question | Classical supercomputer | Quantum computer |
|---|---|---|
| What does it process? | Bits, using classical computing operations. | Qubits, using quantum effects. |
| Where is it useful? | Broadly useful for established workloads, including simulations and calculations that can be handled with classical algorithms. | Potentially advantageous on selected problems for which a suitable quantum algorithm exists; it is not faster for every workload. |
| What limits capability? | Available computing resources and the time a particular classical method takes. | As well as scale, reliable control, connectivity, error rates, and the ability to correct errors. |
| What does the cited coverage establish? | The CBS segment makes a qualitative comparison with future quantum machines; it does not give a supercomputer benchmark for the quoted claim. | The Guardian describes IBM’s scaling and error-correction direction as work toward future fault-tolerant capability, not proof of the quoted comparison. |
The contrast is therefore not “quantum versus classical” as a single winner. A quantum processor would be valuable if it could solve a relevant task better than the strongest practical classical approach, with enough reliability to make the result useful. That would establish an advantage for that task—not across computing as a whole.
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What might future quantum machines be used for?
The 60 Minutes segment and 2023 coverage by The Guardian and TechRadar point to areas where complex physical or chemical behavior could make quantum methods worth investigating:
- Physics and chemistry: modelling systems whose behavior is difficult to calculate accurately with classical methods.
- Molecules and proteins: exploring molecular or protein structures; the CBS segment discusses IBM’s Cleveland Clinic installation as a possible path toward protein-structure work.
- Battery chemistry: IBM Quantum Network participants Mercedes-Benz and Volkswagen have studied chemical reactions inside electric-vehicle battery cells, according to The Guardian.
- Engineering and medicine: longer-term areas in which improved simulations might inform research, rather than established benefits already delivered by general-purpose quantum machines.
- Encryption-related problems: a potential application area, but the cited coverage does not establish that current IBM systems can break real-world encryption.
These examples describe research directions and possible applications, not proof that quantum computers have already produced practical breakthroughs in each field. The Guardian reported that some physics, chemistry, engineering, and medicine problems could take conventional supercomputers “millions of years” compared with a prospective quantum solution. That is a reported possibility for certain problems, not a universal runtime comparison or a demonstrated result for every listed field.
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Are quantum computers useful now?
They are useful as experimental research tools, but the evidence cited here does not show that today’s systems can deliver Gil’s future-machine comparison as a broad, practical capability. TechRadar reported on October 1, 2026, that companies use cloud-accessible quantum systems for early pilots, proprietary algorithms, and preparation for future hardware. Those activities let researchers explore whether a problem suits quantum computing; they do not make every pilot a useful quantum advantage.
Gil also described the machine as “a machine unlike anything we have ever built.” In a separate remark quoted by The Guardian, he said, “We are firmly within the era in which quantum computers are being used as a tool to explore new frontiers of science.” Read together, those statements point to a research tool and a developing technology—not a drop-in replacement for ordinary computers.
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What would need to happen for Gil’s prediction to become practical?
A credible demonstration would need to identify a specific problem, show that a quantum machine can solve it reliably, and compare its performance with the best relevant classical method. For the result to matter outside a narrow demonstration, the calculation would also need to be useful to researchers or an industry, not merely difficult for a classical computer.
The hardware challenge is substantial: future machines need enough well-controlled qubits, workable connections across chips or machines, and effective error correction. IBM’s Heron-related plans, as described by The Guardian in 2023, address aspects of scaling and error correction; that work should not be confused with having already achieved a universal, fault-tolerant quantum computer or the billion-supercomputer result Gil envisioned.
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