Who’s winning the fault-tolerant quantum race: IBM, Google, Microsoft or IonQ?

IBM, Google, Microsoft, and IonQ are racing to build the first fault-tolerant quantum computer. Find out who’s leading and why it matters for investors.

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A four-way contest is underway to determine which technology company will be the first to deliver a fault-tolerant quantum computer—one capable of executing large-scale computations without succumbing to physical qubit errors. International Business Machines Corporation (NYSE: ), Quantum AI, Microsoft Azure Quantum, and Inc. (NYSE: IONQ) are among the leaders vying for quantum supremacy, but their approaches differ in both architecture and roadmap transparency.

The industry has long promised revolutionary breakthroughs in fields such as cryptography, materials science, and financial optimization. However, progress has largely been constrained by noise and decoherence. A fault-tolerant quantum computer would mark the end of the noisy intermediate-scale quantum (NISQ) era and the beginning of practical, scalable quantum applications.

As of mid-2025, each of these firms has disclosed updated timelines, technical breakthroughs, and development challenges, shedding light on how they intend to cross the threshold into fault tolerance by the end of the decade.

Representative image of quantum processor architectures from IBM, Google, Microsoft, and IonQ—each pursuing fault-tolerant computing through distinct hardware strategies in the global quantum technology race.
Representative image of quantum processor architectures from IBM, Google, Microsoft, and IonQ—each pursuing fault-tolerant computing through distinct hardware strategies in the global quantum technology race.

How IBM plans to deliver a fault-tolerant quantum system by 2029

IBM has laid out perhaps the most detailed public roadmap, culminating in the 2029 launch of . The advanced processor is being developed at the company’s new data center in Poughkeepsie, New York, and is projected to execute 100 million quantum operations using 200 logical qubits—approximately 20,000 times the performance of today’s systems.

The American technology company is leveraging quantum low-density parity check (qLDPC) codes to reduce the number of physical qubits required per logical qubit. These codes reduce overhead by up to 90 percent compared to traditional surface codes, enabling more efficient scaling and lower energy costs.

IBM’s roadmap includes a stepwise rollout of interim processors: Quantum Loon (2025), which will test qLDPC infrastructure; Kookaburra (2026), which integrates quantum memory and logic on a modular chip; and Cockatoo (2027), which enables inter-chip entanglement. This modularity is key to scaling quantum systems across multiple nodes without needing physically oversized chips.

Two technical papers published alongside the Starling announcement detail how IBM intends to decode error syndromes in real-time using conventional computing hardware. This real-time decoding architecture is vital to dynamic error correction and ensures fault tolerance doesn’t come at the cost of impractical latency.

What Google is building with its superconducting quantum chips

Google’s Quantum AI division, which stunned the world in 2019 by demonstrating quantum supremacy, has more recently been focused on scaling superconducting transmon qubit systems. In December 2024, the tech giant introduced its Willow processor, a 105-qubit chip that reportedly executed a benchmark task impossible for classical supercomputers to replicate.

Google’s six-stage roadmap toward fault tolerance includes achieving a stable logical qubit, demonstrating universal gate operations, and expanding to multi-chip connectivity. While it has not committed to a specific fault-tolerant target date, the Willow benchmark represented an exponential error suppression milestone.

However, Google has acknowledged the engineering complexity of fault-tolerant systems, likening the effort to constructing a CERN-scale scientific facility. Key challenges include dense qubit wiring, cryogenic infrastructure, and managing crosstalk between entangled qubit groups. Despite these, Google remains a credible contender due to its deep in-house physics expertise and proven chip fabrication capabilities.

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Why Microsoft is betting on topological qubits and Majorana particles

Microsoft Azure Quantum is pursuing a fundamentally different approach: topological qubits constructed from Majorana zero modes. In February 2025, the enterprise software developer unveiled its Majorana 1 chip, which demonstrated the presence of these exotic particles in a hybrid indium arsenide–aluminum nanowire system. This announcement marked the first credible evidence of stable topological quantum behavior.

Unlike superconducting or ion-trap systems, Microsoft’s topological qubits aim to encode quantum information in spatially separated quantum states, offering hardware-level error suppression. While the current prototype only supports eight qubits, Microsoft’s roadmap includes expansion through linear arrays, universal Clifford gate sets, and eventually large-scale logical qubit construction via lattice surgery.

From an architectural standpoint, topological qubits may offer superior coherence times and lower logical error rates than existing designs. However, Microsoft’s challenge lies in scaling up from small, protected systems to multi-qubit processors with high-fidelity entanglement. Its integration with Azure Quantum Cloud services, the Q# programming language, and hybrid AI-QC workloads places it in a unique position to capitalize once the hardware matures.

Where Quantinuum and IonQ stand in the fault-tolerant race

Quantinuum, a spinout of Honeywell’s quantum business, is focused on trapped-ion architectures and aims to launch Apollo, its first fault-tolerant quantum system, by 2030. The architecture benefits from naturally long coherence times and low gate error rates, though its scalability remains limited by laser-based control mechanisms and slower gate speeds.

IonQ Inc., another trapped-ion specialist, has leaned into commercialization. While its hardware is not yet fault-tolerant, it is actively selling quantum compute cycles to enterprise customers via Amazon Braket and other platforms. Its focus on application-layer revenue in machine learning, logistics, and quantum chemistry keeps it relevant, but its roadmap for fault tolerance lacks the rigor or specificity of IBM, Google, or Microsoft.

Quantinuum has secured significant private funding and published peer-reviewed benchmarks for error rates and entanglement fidelity. In contrast, IonQ continues to be viewed as a retail-heavy, speculative asset despite early adoption in software pilots.

How do their technical strategies differ?

The five leading firms diverge sharply in how they define and approach error correction.

IBM relies on qLDPC codes, which allow error suppression using far fewer physical qubits, enabling modular scaling with realistic energy and infrastructure constraints. This method, validated in Nature and recent arXiv preprints, is seen as among the most promising for near-term deployment.

Google uses superconducting qubits with surface codes, which are well-understood and offer good performance at small scale but require large hardware overhead. Microsoft’s topological qubits, still experimental, promise inherent error resilience but face long development timelines.

Quantinuum and IonQ, with trapped-ion designs, emphasize high-fidelity qubit operations and slow gate speeds, which are beneficial for error rates but present challenges in clock speed and scaling across distributed systems.

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What are institutional investors watching in the quantum sector?

Investor sentiment around quantum computing remains long-cycle and speculative. IBM is currently trading at a forward P/E ratio of approximately 14.2x, with top holders like Vanguard and BlackRock maintaining positions. Analysts have assigned the stock a Hold rating, citing stable cash flows, a 4.1% dividend yield, and optional upside from the Starling initiative.

Microsoft remains favored by institutional investors for its AI and cloud growth story, with its quantum ambitions seen as a strategic hedge. Google’s Alphabet Inc. retains strong buy ratings on the strength of its diversified deep tech bets, including quantum.

IonQ, which went public via SPAC, remains volatile, with limited institutional participation and an outsized retail presence. Quantinuum, currently privately held, may consider a public listing by 2026 if fault-tolerant milestones are met.

Derivatives activity—particularly options volume in IBM and Microsoft—has seen a mild uptick following major roadmap announcements, indicating growing interest among hedge funds in quantum-linked innovation plays.

What milestones should the industry track next in the race to fault tolerance?

The next 12 to 24 months will be pivotal in determining whether any major technology company can credibly claim to be on track to deliver a fully fault-tolerant quantum computer before the end of the decade. Each of the sector’s front-runners—IBM, Google, Microsoft, Quantinuum, and IonQ—is preparing key demonstrations that, if successful, will serve as proof points for their respective architectures and strategic roadmaps.

By mid-2026, International Business Machines Corporation is expected to unveil IBM Quantum Kookaburra, the first modular quantum processor in its roadmap. Kookaburra is designed to combine quantum memory and logic operations within a unified, scalable chip. This milestone will allow IBM to demonstrate early evidence of modular error correction using qLDPC codes—a critical capability for constructing larger systems like the eventual IBM Quantum Starling platform. If Kookaburra performs as planned, it will validate IBM’s commitment to a multi-chip future based on real-time error decoding, low-overhead logical qubits, and modular hardware interconnectivity. Investors and quantum researchers will be watching closely for data on error rates, gate fidelities, and integration with decoding backends powered by FPGAs or ASICs.

Google is also expected to release a successor to its Willow processor by 2026. While details remain under wraps, the next-generation superconducting chip may push beyond Willow’s 105-qubit design and demonstrate new benchmarks in multi-chip fidelity. Google’s strategy focuses on error suppression using surface codes and high-coherence superconducting qubits, so scaling across multiple interconnected chips would be a significant leap. The industry will likely scrutinize the processor’s ability to maintain qubit fidelity during entanglement across chip boundaries—an essential step toward a distributed, fault-tolerant quantum system. Progress here could also influence Google’s broader ambitions in AI–quantum hybrid integration via its cloud infrastructure.

Microsoft, on the other hand, is concentrating efforts on advancing its topological qubit platform. Following the February 2025 announcement of its Majorana 1 chip, which demonstrated the first credible signal of Majorana zero modes, the enterprise software and cloud leader is targeting the next phase: validating braided operations in linear and lattice-based Majorana arrays. Braiding, the act of exchanging Majorana particles in a specific spatial pattern, is central to performing fault-tolerant gate operations in topological quantum systems. If Microsoft succeeds in demonstrating this technique with high repeatability and minimal decoherence, it will not only solidify its long-term advantage in hardware error suppression but also position its topological roadmap as a compelling alternative to the more resource-intensive superconducting and ion-trap models.

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Meanwhile, Quantinuum is expected to continue refining its trapped-ion technology platform, with a focus on demonstrating high-fidelity logical qubits and scalable gate operations. Its Apollo system, targeted for release by 2030, will require the successful execution of millions of fault-tolerant operations using modest physical infrastructure. Interim milestones over the next two years will include published error rates, circuit depth benchmarks, and operational data on mid-circuit measurements—each of which will serve as evidence that the trapped-ion architecture can be reliably scaled in commercial environments. Quantinuum’s partnership momentum and increased enterprise interest in chemistry simulations and cryptography workloads suggest growing institutional confidence, even as the path to fault tolerance remains demanding.

IonQ, the publicly traded trapped-ion quantum computing firm, may not be as close to fault-tolerant milestones as its larger competitors, but the company is steadily expanding its customer pilot programs. Over the next year, IonQ is likely to focus on demonstrating repeatable use cases for cloud-deployed quantum workloads via Amazon Braket, Microsoft Azure, and its own cloud API. Areas such as quantum-enhanced machine learning, logistics optimization, and materials modeling are expected to be areas of growth. While it has yet to outline a clear path to logical qubit construction, IonQ’s go-to-market strategy relies on hybrid architectures and commercial traction, which could serve as a foundation for hardware investments in subsequent phases.

Collectively, these milestones will inform whether any of these firms are truly positioned to declare fault tolerance achieved by 2029. For investors and enterprise stakeholders, the next 18–24 months represent a narrowing window in which progress must transition from simulation to systems. Analysts and sector observers will evaluate each announcement for concrete advancements—not only in logical fidelity and error rates, but also in power efficiency, fabrication yield, and real-time decoder integration. The fault-tolerant quantum race is no longer theoretical—it is now a battle of execution, infrastructure maturity, and architectural bets coming to fruition.


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