IBM and AWS Sell Quantum Cloud. Google Still Doesn’t
Your CTO just asked for a quantum computing budget line for next year. You pull up a headline claiming IBM, Google, and AWS all sell quantum as a cloud service, and you build a three-way comparison deck around it. That deck is wrong before slide two. Google will not sell you access to its Willow chip in 2026, no matter what your procurement team offers to pay.
This matters because the mistake is easy to make and expensive to repeat. Quantum cloud computing has quietly split into distinct commercial tiers, and mixing them up means budgeting for a product that does not exist. Here is what IBM, AWS, and Google actually sell today, what it costs, and which one fits the workload you are actually running.
In This Article
The Google Correction Everyone Skips
What IBM Quantum Actually Sells
What AWS Braket Actually Sells
The Benchmark That Actually Matters
Why Qubit Count Is a Marketing Trap
Which Provider Fits Your Workload
Frequently Asked Questions
The Google Correction Everyone Skips
IBM and AWS genuinely sell commercial quantum cloud access right now. Anyone with a credit card and a Qiskit or Braket SDK install can run jobs on real hardware this afternoon. Google does not offer that. Its 105-qubit Willow processor is only reachable through the Willow Early Access Program, a selective research initiative, not a purchasable service. Applications closed on May 15, 2026, selections went out July 1, and the program exists to identify research partners for high-impact projects, not paying customers.
What Google Cloud does sell is different: marketplace access to third-party quantum hardware, including systems from Pasqal. That is a legitimate quantum cloud story. It just is not the same story as “buy time on Willow,” and conflating the two sends budget planning in the wrong direction from the first paragraph.
Why this correction matters for your budget: If your procurement plan assumes Google is a third purchasable option alongside IBM and AWS, you are planning around a product Google is not selling. Treat Google Cloud’s marketplace quantum hardware as the real 2026 option, and treat Willow as a research relationship you would have to apply for, not procure.
What IBM Quantum Actually Sells
IBM’s production hardware for the IBM Quantum Network is Heron r2, a 156-qubit processor with a median two-qubit gate error rate near 0.3%. The newer Nighthawk processor, announced in November 2025, runs 120 physical qubits on a square lattice with 218 next-generation tunable couplers, and IBM is targeting quantum advantage by the end of 2026 with an initial complexity target around 5,000 two-qubit gates, scaling toward 10,000 by 2027.
IBM sells access through four tiers, and the pricing gap between them is the actual decision that matters for most teams:
| Plan | Rate | Commitment |
|---|---|---|
| Pay-As-You-Go | ~$96/minute | None |
| Flex | ~$72/minute | $30,000 minimum, 400+ minutes/year |
| Premium | ~$48/minute | 5,200+ minutes/year |
That structure only makes sense once you map it to how often you actually run jobs. A team testing an algorithm twice a month has no business locking into a $30,000 Flex commitment. A team running continuous research cadence is bleeding money on Pay-As-You-Go rates.
Nighthawk vs. Heron: Which One Are You Actually Renting?
Most IBM Quantum Network access in 2026 still routes through Heron r2 for production workloads. Nighthawk is the forward-looking system IBM is using to chase its 2026 advantage claim, and it is worth asking your IBM rep directly which processor your plan tier actually reserves time on, because the marketing material does not always make the distinction obvious.
What AWS Braket Actually Sells
AWS Braket takes the opposite approach to IBM: no subscription tiers, no minimum commitment, just a per-shot and per-task pricing model across multiple hardware vendors. That multi-vendor structure is the real differentiator, and the price spread across vendors is bigger than most buyers expect.
| Hardware | Per-Shot Rate | Per-Task Fee | Hourly Reservation |
|---|---|---|---|
| IonQ Forte | $0.08 | $0.30 | $7,000/hr |
| AQT IBEX-Q1 | $0.0235 | $0.30 | $4,800/hr |
| Rigetti Cepheus | $0.000425 | $0.30 | $4,100/hr |
| IQM Garnet | $0.00145 | $0.30 | $3,000/hr |
| QuEra Aquila | $0.01 | $0.30 | $2,500/hr |
Do the math on a 10,000-shot circuit and the gap gets uncomfortable fast. The same circuit costs roughly $300 on a trapped-ion system like Aria and roughly $5 on a superconducting Rigetti system, a ratio north of 60x for what buyers often treat as an interchangeable choice. That gap is driven almost entirely by qubit modality, not by which vendor happens to be having a good pricing quarter, according to independent pricing analysis at quantumcomputingcost.com, verified against primary AWS pricing pages in June 2026.
The Benchmark That Actually Matters
Pricing tables tell you what quantum cloud access costs. They do not tell you whether it works. For that, the clearest 2026 evidence comes from JPMorgan Chase and the AWS Center for Quantum Computing, who published “Quantum-Informed Portfolio Selection” on July 1, 2026, describing a 225-asset portfolio diversification problem run on Quantinuum’s 98-qubit Helios trapped-ion computer.
The detail that should reshape how you think about procurement: standalone QAOA, the algorithm most quantum-optimization marketing leans on, failed completely on the hardest indices in the study. Zero percent success rate. JPMorgan’s team only got usable results by switching to a hybrid algorithm called qReduMIS that combines classical and quantum computation.
Marco Pistoia, Head of Global Technology Applied Research and Head of Quantum Computing at JPMorgan Chase, has credited the bank’s access to NVIDIA GPU-based supercomputing through Argonne National Laboratory as central to running the large-scale numerical studies behind this research. Source: JPMorganChase Technology Blog / arXiv, arxiv.org/html/2607.01037
Read our full breakdown of the 98-qubit result in JPMorgan’s Quantum Computing Leap: 98-Qubit Data for the complete methodology.
Why Qubit Count Is a Marketing Trap
Here is the number that should worry anyone benchmarking providers on qubit count alone: a five-qubit system running at 99.99% two-qubit gate fidelity can execute deeper, more reliable circuits than a 1,000-qubit system stuck at 99% fidelity. Qubit count is the most heavily marketed metric in this industry and, by most technical accounts, the least useful one for predicting whether your workload will actually complete successfully.
Robbie King, a doctoral researcher in quantum computing at Caltech, has framed the honest industry question at conferences this way: if you handed most businesses a working quantum computer tomorrow, could they actually run the algorithm they think they need? For most of the field right now, the honest answer is not really.
Scott Aaronson, the Schlumberger Centennial Chair of Computer Science at UT Austin and quantum computing’s most credible public skeptic, has struck a notably less skeptical tone on one specific point. He has said that people whose judgment on hardware and error correction he trusts more than his own now believe a fault-tolerant quantum computer capable of breaking deployed cryptography could arrive around 2029.
On the broader commercial hype cycle, Aaronson remains the field’s most credible skeptic, even as he acknowledges genuine hardware progress from Google, Quantinuum, and QuEra. Source: scottaaronson.blog, May 1, 2026
That is a narrow alarm about cryptography timelines, not a blanket endorsement of near-term commercial ROI. Aaronson treats the ROI question with exactly the skepticism you would expect from him.
The failure mode this creates: A team picks a high-qubit-count superconducting provider for a workload whose required circuit depth exceeds its coherence-time budget. They burn through a $30,000 IBM Flex Plan minimum on results that never converge, and conclude “quantum doesn’t work.” The actual problem was a hardware-topology mismatch, the exact class of failure JPMorgan’s hybrid workaround was built to route around.
Which Provider Fits Your Workload
Stop asking which provider is best. Ask which billing model matches how often you actually run jobs.
| Your pattern | Best fit | Why |
|---|---|---|
| Occasional experimentation, multiple hardware types | AWS Braket | No commitment, per-shot billing, multi-vendor access |
| Sustained, continuous research cadence | IBM Premium | Lowest per-minute rate, rewards high usage volume |
| Bursty, project-based work | IBM Flex | Mid-tier rate without a full annual commitment |
| Research partnership, not production workload | Google Willow Early Access | Only path to Willow, but requires application and selection |
Notice what is missing from that table: qubit count as a selection criterion. It should not be the first filter, and on current evidence it should not be a filter at all until you have confirmed your workload’s actual coherence and circuit-depth requirements against the hardware’s real fidelity numbers, not its headline spec sheet.
Frequently Asked Questions
Which is better, IBM or Google quantum computer?
They are not directly comparable through cloud access in 2026. IBM sells commercial cloud access across four plans to its Heron and Nighthawk processors, while Google’s Willow chip is only reachable through a selective, non-commercial Early Access research program, not a purchasable cloud service.
How much does AWS Braket cost?
AWS Braket charges no upfront fee. Pricing combines a flat $0.30 per-task fee with per-shot rates that vary by hardware, from $0.000425 per shot on Rigetti Cepheus to $0.08 per shot on IonQ Forte, plus optional hourly reservations ranging from $2,500 to $7,000 per hour.
Is quantum computing available on the cloud?
Yes. IBM Quantum Platform and AWS Braket both offer commercial cloud access to real quantum hardware from vendors including IonQ, Rigetti, IQM, and Quantinuum, with plans ranging from pay-as-you-go rates to enterprise subscription tiers.
What is the best quantum cloud provider for enterprises?
There is no single best provider. AWS Braket suits intermittent, multi-vendor experimentation through per-shot pricing. IBM Quantum suits sustained research with predictable per-minute billing. The right choice depends on workload cadence and circuit-depth requirements, not headline qubit counts.
Is quantum computing overhyped?
Partly. Hardware progress on qubit counts, gate fidelity, and error correction has outpaced expert predictions from a decade ago. The algorithms needed to turn that hardware into business value, and the talent pool to build them, both lag well behind current hardware capability.
What This Means Going Into 2027
Three things are worth watching over the next 6 to 18 months. First, whether IBM actually hits its end-of-2026 quantum advantage target on Nighthawk, since that date is close enough to check. Second, whether Google converts any Willow Early Access research partnerships into a genuine commercial product, which would change this entire comparison. Third, whether more enterprise teams follow JPMorgan’s lead into hybrid quantum-classical approaches rather than waiting for pure quantum algorithms to catch up to the hardware.
Here is what you now know that the “IBM, Google, and AWS all sell quantum cloud” headline does not tell you: only two of those three companies are actually selling anything you can buy today, the pricing models are structured for completely different usage patterns, and the algorithm running on the hardware matters more than the qubit count printed on the spec sheet. Budget accordingly.
Quantum computing pricing, hardware, and access models are shifting fast enough that this comparison will need revisiting well before 2027. Subscribe to The Neural Loop at neuralwired.com/newsletter to get the next update before your competitors do.
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