The Superconducting Race

In early 2025, USTC unveiled Zuchongzhi 3.0, a 105-qubit superconducting processor, and claimed a random-circuit-sampling task that would take the Frontier supercomputer some 6.4 billion years, roughly a million times harder to simulate than Google’s earlier results.^[1] Weeks earlier, Google had unveiled Willow, also a 105-qubit chip.^[2] The headlines framed it as China pulling ahead. The reality is that the two chips were racing toward different finish lines.

Two scoreboards

Zuchongzhi 3.0’s achievement is a sampling benchmark: raw evidence that its output is hard for a classical computer to reproduce.^[1] Willow’s headline result is something Zuchongzhi 3.0 did not attempt at all, quantum error correction “below threshold.” Google showed that as it encoded information across larger and larger grids of qubits, the error rate fell by roughly half at each step, the property a useful quantum computer requires, and a goal pursued since 1995.^[2][3]

Both chips carry 105 qubits. One won a sprint that may not matter; the other took a step toward the race that does.

So the “China beats Google” framing conflates two things. On sampling, Zuchongzhi 3.0 claims a larger classical-hardness gap — a gap of the same kind that classical algorithms have repeatedly shrunk. On error correction, the metric that actually gates fault-tolerant computing, Google set the benchmark and China’s chip is not yet in the comparison. Even Willow’s own sampling number, five minutes against an almost unfathomable supercomputer estimate, has no known real-world use.^[4]

Why does error correction matter more than a bigger sampling number? Because every physical qubit is noisy, and without correction the errors accumulate faster than a longer computation can outrun, so raw qubit counts buy nothing useful on their own. “Below threshold” is the proof that adding qubits can make a logical qubit more reliable rather than less, the precondition for any machine that runs a real algorithm. That is why a chip that wins a sampling sprint and a chip that takes a step on error correction are not on the same road: one is a demonstration of hardness, the other a down-payment on usefulness.

Reading it as an investor

Qubit counts and sampling speedups make headlines; error rates make computers. The single most useful filter for quantum news is to ask which scoreboard a claim is on. China is genuinely at the hardware frontier on qubit count and gate fidelity. But leadership on the metric that matters, scalable error correction, is still contested, and that is where we focus our attention and our skepticism.