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Head to headIBM vs Google
Both build superconducting quantum chips, so their machines can be compared fairly. The difference is in strategy: IBM sells access and publishes a year-by-year roadmap, while Google keeps its chip in-house and aims for landmark experiments.
Can they be compared? Mostly yes. Both use superconducting qubits, so accuracy, speed and qubit counts measure the same kind of hardware. Their error-correction plans use different codes, so error-correction results are only compared where QubitBenchmark has grouped them as comparable.
Side by side
| Topic | IBM | Google Quantum AI |
|---|---|---|
| Approach | Superconducting | Superconducting, Neutral atom |
| Most accurate | #3 | |
| Error-corrected qubits | ||
| Most qubits | #2 | #3 |
| Fastest | #1 | |
| Use it today | #1 | |
| Latest machine | Nighthawk (120 qubits, 2025–26) and Heron (156 qubits) | Willow (105 qubits, 2024) |
| Can you use it? | Yes: IBM Quantum cloud, plus systems installed at partner sites | No public access; selected research groups only |
| Error-correction plan | qLDPC codes, which need long-range links on the chip (tested on the experimental Loon chip) | Surface code; showed errors falling as the code grew (Nature, December 2024) |
| Next big promise | Starling: a fault-tolerant system with 200 logical qubits by 2029 | A long-lived logical qubit (Milestone 3); no date given |
| Delivery record | Detailed public roadmap. Several milestones delivered on time or early; Kookaburra was redefined and moved to 2026 | Milestones 1 and 2 delivered; dates for what comes next aren't published |
How they differ
IBM and Google both build quantum chips from superconducting circuits cooled to near absolute zero. That makes them one of the fairest comparisons in the field: when they report accuracy or speed, they're measuring the same kind of machine.
Where they part ways is strategy. IBM runs a business: its machines are on a public cloud, it installs systems at partner sites, and it publishes a detailed year-by-year roadmap that makes its promises easy to check. Google keeps Willow for its own scientists and a few chosen research groups, and focuses on headline experiments, such as its 2024 error-correction result and its 2025 "Quantum Echoes" claim (our Reality Check).
Who's ahead
It depends on the race. The table above shows where each stands this month on published evidence. On error correction, Google's surface-code result is peer-reviewed. IBM's newer approach promises to need far fewer qubits per logical qubit, but its key demonstrations are still company-reported. For a business that wants to try a quantum computer today, IBM is the practical answer, because Google offers no public access.
Bottom line: IBM is the one you can use today and hold to a schedule. Google has the stronger landmark results. Neither has a useful error-corrected machine yet.
Sources
- IBM delivers new quantum processors, software, and algorithm breakthroughs on path to advantage and fault tolerance, IBM Newsroom, 12 November 2025
- IBM connects its first modular cryogenic systems in milestone toward fault-tolerant quantum computing, IBM Newsroom, 19 August 2026
- IBM quantum roadmap 2026, IBM
- Meet Willow, our state-of-the-art quantum chip, Google blog, 9 December 2024
- Google Quantum AI error-correction milestones, Google Quantum AI