Google Quantum AI’s latest processor, Willow, completed a benchmark computation in under five minutes. The same task would take Frontier, one of the world’s fastest classical supercomputers, an estimated 10 septillion years. That’s 10 followed by 25 zeros, a number so large it makes the age of the universe (roughly 14 billion years) look like a rounding error.
The 105-qubit superconducting chip represents a genuine breakthrough in quantum error correction, the field’s most stubborn bottleneck. But Google CEO Sundar Pichai offered a reality check in February 2025: practical, useful quantum computers are still 5 to 10 years away.
What Willow actually did
The benchmark in question is called random circuit sampling, a task specifically designed to test quantum processors against classical machines. Google announced the Willow results on December 9, 2024, alongside a peer-reviewed paper published in Nature.
Willow broke that cycle. By increasing the “code distance” from 5 to 7 (a measure of how many physical qubits protect each logical qubit), Google’s team reduced the logical error rate by a factor of approximately 2.14. This is the first time anyone has successfully maintained performance below what’s known as the surface code threshold at both distance 5 and distance 7.
Even more notable: Willow’s distance-7 logical memory outlasted the lifetime of its best individual physical qubit by a factor of 2.4.
From Sycamore to Willow
This isn’t Google’s first quantum milestone. Back in 2019, its 53-qubit Sycamore processor became the first to demonstrate “quantum supremacy,” completing a calculation that would have taken a classical supercomputer thousands of years.
Willow makes the Sycamore result look quaint by comparison. The gap between quantum and classical performance widened from thousands of years to 10 septillion years, even under what Google describes as conservative assumptions. Hartmut Neven, founder and lead of Google Quantum AI, oversaw both efforts.
The 5-to-10 year gap
Pichai’s February 2025 comments placed the quantum computing trajectory in context by comparing it to artificial intelligence’s long gestation period. AI research hummed along for decades before deep learning hit escape velocity in the early 2010s. Pichai suggested quantum computing sits at a similar inflection point.
For the cryptography world, the implications are worth monitoring. Modern encryption relies on mathematical problems that classical computers can’t efficiently solve. A sufficiently powerful, error-corrected quantum computer could theoretically crack widely used encryption schemes like RSA and elliptic curve cryptography. Willow is not that computer. But it demonstrates that the error correction problem is yielding to engineering.
Post-quantum cryptography standards are already in development. The US National Institute of Standards and Technology has been working on quantum-resistant algorithms for years, and several were finalized in 2024.