A quantum computer solves an economically valuable problem faster than classical computers before 2030.
While quantum supremacy has been demonstrated on synthetic benchmarks, practical utility remains elusive. Resolution requires verified advantage on a real-world scientific or business problem.
Across 6 frontier models answering independently, the panel thinks this is unlikely: the median is 20%.
They do not agree: GPT puts it at 58% and Claude at 10%, 48 points apart. A spread that wide usually means the question turns on something none of them can see yet.
Nothing is settled until 27 Oct 2031, when the outcome is checked against sources and every number above gets a permanent score.
What each one said
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GPTOpenAI
It hinges on fault-tolerant hardware reaching enough logical qubits to beat optimized classical workflows on a paid-use case.
- Google, IBM, Quantinuum and startups must deliver error-corrected systems and independent end-to-end benchmarks before 2030.
- Benchmark supremacy is established, but no real workload has yet beaten classical methods on cost, speed, and verifiable output.
- A 2027–28 demonstration of sustained logical qubits with low logical error rates would materially raise the odds.
58% -
GeminiGoogle
Turns on whether neutral-atom or superconducting error-mitigated processors surpass classical HPC heuristics in chemistry by 2029.
- No commercially viable advantage exists today as classical tensor network algorithms continually outpace noisy quantum hardware.
- Hardware roadmaps from IBM, QuEra, and Google target 1,000+ logical qubits around 2030, making commercial utility tight before 2030.
- Verified chemical catalysis or battery material calculations published in Nature with industry adoption would flip my view.
38% -
DeepSeekDeepSeek
Whether error-corrected hardware reaches ~100 logical qubits and a real chemistry or optimization problem beats classical methods by 2031.
- Google, IBM, Quantinuum, and PsiQuantum must convert physical-qubit milestones into fault-tolerant logical qubits; IBM's Starling roadmap targets 200 logical qubits by…
- Classical baselines keep improving too—tensor-network and GPU-accelerated simulators have repeatedly erased claimed quantum advantages, so any candidate must beat a…
- Base rate is low: since 2019's supremacy claims, zero peer-reviewed cases show economic value on a real problem, and the field's own roadmaps put useful applications in…
22% -
GrokxAI
Error-corrected hardware must scale enough by 2029 to beat classical on a verified real chemistry or optimization task.
- IBM/Google/Quantinuum roadmaps put useful logical-qubit counts after 2030; three years is too short for the needed error-correction overhead.
- Decades of missed QC timelines set a low base rate; NISQ devices have shown no economic advantage despite supremacy claims.
- A sudden analog-simulator win on materials or a peer-reviewed chemistry speedup would shift the odds upward.
18% -
ClaudeAnthropic
Hinges on whether error-corrected or NISQ devices hit a verified real-world advantage by 2031, not just synthetic benchmarks.
- Current demos (Google, IBM, Quantinuum) remain synthetic sampling tasks without economic value, and error correction is still in early logical-qubit scaling stages.
- Industry roadmaps (IBM, Google) target meaningful fault-tolerant advantage closer to 2029-2033, with practical chemistry/optimization wins still speculative.
- A surprise breakthrough in quantum chemistry or optimization with verified classical-intractability would flip this, but no credible near-term candidate exists yet.
10% -
QwenAlibaba
Requires fault-tolerant logical qubits solving a real problem, but current systems have only single-digit logical qubits.
- IBM and Google roadmaps place useful fault-tolerant computation at 2030–2033; 'before 2030' cuts off the optimistic edge of those timelines.
- Every NISQ-era advantage claim to date (D-Wave optimization, IBM utility experiments) has been matched or beaten by improved classical algorithms within months.
- A surprise breakthrough in error-correction overhead reduction or a novel algorithm with shallow circuit depth for a specific industrial problem would be needed to move…
10%
6 of 6 models answered · 48 points between the highest and lowest. None was shown the market price.
Question sourced from a news sweep on 28 Oct 2026. Forecast by google/gemini-3.8-flash, anthropic/claude-sonnet-5, openai/gpt-5.6-terra, x-ai/grok-4.6, deepseek/deepseek-v4.1-flash, qwen/qwen3.8-max-0902 via OpenRouter.