At the 2025 Quantum Developer Conference, IBM Research Director Jay Gambetta and colleagues outlined advances in algorithms, hardware and software designed to make it easier to achieve quantum advantages. The presentation featured three candidate advantage experiments—observable estimation, variational algorithms, and efficient classical verification problems—that are currently being pursued through a new, open, community-led initiative developed in collaboration with Flatiron, BlueQubit, and Algorithmiq. This tracker systematically assesses potential quantum advantages over leading classical methods, focusing on metrics such as efficiency, cost-effectiveness and accuracy, as IBM argues that rigorous validation remains a critical requirement to demonstrably outperform classical computation.
Quantum Advantage: Current status and framework
Quantum advantage – where quantum computers are proven to outperform classical computers – is getting closer to reality, but is not an easy goal. IBM is actively pursuing candidates in the areas of observable estimation, variational algorithms, and efficient classical verification problems. An important framework focuses on rigorous validation And measurable improvements in efficiency, cost or accuracy. An open, community-led Advantage Tracker is now available to systematically compare quantum results with leading classical methods, promoting transparency and collaborative progress.
Recent hardware advances are critical to scaling to advantage. The new 120-qubit IBM Quantum Nighthawk chip features a square qubit topology with 218 couplers – a 30% increase in circuit complexity compared to previous designs. IBM also unveiled improvements to the Heron processor, which reached 330,000 CLOPS (compared to 200,000 at the end of 2024) and demonstrated significant speedups in quantum utility experiments – over 100 times faster than in 2023. This represents a concrete step towards tackling more complex problems.
Software optimization is equally important. The latest Qiskit SDK v2.2 offers an 83x increase in transpilation speed compared to competitor Tket. New features like circuit annotations and the Samplomatic package give developers greater control over error mitigation, reducing sampling overhead by up to 100x with techniques like probabilistic error suppression. Dynamic circuits that integrate classic mid-run calculations are now feasible at scale – showing up to 25% accuracy improvement with a 58% reduction for two-qubit gates.
New hardware: IBM Quantum Nighthawk and Heron
IBM introduced the 120-qubit “Nighthawk” processor, an important step toward achieving quantum advantage. Notably, Nighthawk features a square qubit topology with 218 couplers – an increase over Heron's 176 – allowing the design of 30% more complex circuits with fewer SWAP gates. This improved connectivity aims to tackle larger, more challenging problems. IBM plans revisions that can power circuits with 5,000, 7,500, 10,000 and eventually 15,000 quantum gates, aiming for a milestone of 5,000 gates by the end of 2025.
In addition to Nighthawk, IBM highlighted progress with the “Heron” processor, which is now in its third revision. This version has the lowest two-qubit gate errors to date: 57 of 176 couplings achieved less than one error per 1,000 operations. The entire Heron fleet now delivers 330,000 CLOPS (Quantum Computational Operations per Second), a significant increase from 200,000 at the end of 2024. This increased performance allowed the quantum utility experiment to be carried out in less than 60 minutes – over 100 times faster than in 2023.
Software is equally important, and IBM's open source Qiskit SDK continues to lead the way in performance. Benchmarks show that Qiskit v2.2 is 83 times faster at transpiling than its competitor Tket 2.6.0. New tools such as the “Samplomatic” package provide greater control over circuit tuning and error mitigation, reducing sampling overhead by 100-fold for techniques such as probabilistic error suppression. These advances demonstrate a commitment to a collaborative, hybrid quantum classical approach – essential to realizing practical quantum advantages.
Qiskit SDK: Performance and latest updates
The IBM Quantum team recently unveiled the 120-qubit Nighthawk processor, an important step toward scaling quantum advantage. Nighthawk features a square qubit topology with 218 couplers – a 30% increase over the Heron chip – enabling more complex circuit designs with fewer SWAP gates. Future revisions aim to power circuits with 5,000, 7,500, 10,000 and ultimately 15,000 quantum gates, with a milestone of 5,000 gates predicted by year's end. This focus on modularity and performance is critical to tackling increasingly complex problems.
In addition to hardware advances, the open source Qiskit SDK remains a cornerstone of IBM's strategy. Benchmarks show Qiskit v2.2 to be 83x faster at transpiling than the Tket 2.6.0 SDK, underscoring its continued performance leadership. New features such as circuit annotations and the Samplomatic package provide granular control for circuit optimization and advanced error reduction techniques. This allows developers to explore and refine circuits more efficiently, accelerating the path to demonstrable quantum advantages.
Qiskit's recent improvements focus on dynamic circuits – circuits that integrate classic mid-run operations. Using circuit annotations, IBM demonstrated up to 25% accuracy improvement and a 58% reduction in two-qubit gates for more than 100 qubits using dynamic circuits for a 46-site Ising model simulation. In addition, Samplomatic reduces the sampling overhead of probabilistic error suppression (PEC) by 100 times. These improvements demonstrate the synergistic potential of combining quantum and classical computing for significant gains.
Scaling advantage with dynamic circuits
IBM's pursuit of quantum advantage focuses on hardware capable of running increasingly complex circuits. The new 120-qubit Nighthawk chip features a square-qubit topology with 218 couplers – a 30% increase over previous designs – enabling developers to solve larger problems with fewer SWAP gates. Importantly, IBM aims to scale Nighthawk's performance, eyeing revisions that can run circuits with 5,000, 7,500, 10,000 and eventually 15,000 quantum gates, with a milestone of 5,000 gates forecast by year-end 2025.
Beyond the number of pure qubits, software optimization is crucial. The open source Qiskit SDK v2.2 is now 83x faster at transpiling than competing frameworks like Tket. This speed boost, combined with new tools such as the Samplomatic package, allows for more granular control over circuit execution and the implementation of advanced error reduction techniques. In particular, Samplomatic enables tailored circuit randomization, significantly reducing the overhead associated with methods such as probabilistic error suppression (PEC) – up to a 100x improvement.
An important advance lies in the development and deployment of dynamic circuits. These circuits integrate classical calculations while Quantum execution, which uses measurements at the center of the circuit to make conditional changes. Demonstrations at the QDC showed that dynamic circuits using features such as delayed timing and stretched operations produce up to 25% more accurate results, with the number of two-qubit gates reduced by 58% at scales above 100 qubits – illustrated by a 46-site Ising model simulation.
Advanced error reduction techniques
Recent advances at IBM Quantum are heavily focused on reducing scaling errors, which are critical to achieving demonstrable quantum advantages. The new IBM Quantum Nighthawk processor with 120 qubits with square topology and 218 couplers enables 30% more complex circuit designs with fewer SWAP gates. Additionally, improvements to the Heron processor now deliver less than one error in 1000 operations on 57 of its qubit couplings, and the fleet now reaches 330,000 CLOPS – a significant increase from 200,000 last year.
Beyond hardware, Qiskit SDK v2.2 demonstrates impressive software performance, transpiling circuits 83 times faster than competing SDKs such as Tket. Crucially, the Samplomatic package provides granular control over circuit regions via annotations, enabling efficient implementation of advanced error mitigation techniques. This allows developers to efficiently apply methods such as probabilistic error suppression (PEC) while minimizing overhead – reducing PEC sampling requirements by up to 100x.
Dynamic circuits integrated by Qiskit's annotation capabilities represent a significant advance. By integrating classical operations at runtime, these circuits achieved up to 25% more accurate results with a 58% reduction in two-qubit gates at scales larger than 100 qubits. Demonstrations using an Ising model simulation at 46 locations illustrate the concrete advantages of dynamic circuits over static utility-scale approaches and prove that combined quantum and classical approaches are the key to realizing practical quantum computers.
HPC integration and the quantum community
IBM is prioritizing integration between quantum hardware and high performance computing (HPC) to accelerate the path to quantum advantage. The newly introduced 120-qubit Nighthawk processor features a square-qubit topology with 218 couplers – a 30% increase in circuit complexity capacity compared to previous designs. In addition to the hardware, the software is also crucial. Qiskit SDK v2.2 demonstrates an 83x transpilation speed improvement compared to competitor Tket 2.6.0, demonstrating a commitment to robust software tools for better workloads.
Scaling quantum advantage requires advanced error reduction techniques, and IBM delivers tools like Samplomatic. This package enables individual circuit randomization and significantly reduces the sampling overhead of probabilistic error rejection (PEC) – by up to 100x – enabling more efficient noise reduction. Demonstrations showed a 25% improvement in accuracy and a 58% reduction in two-qubit gates at scales of 100+ qubits using dynamic circuits – demonstrating utility-scale advantages over static designs.
Propulsion isn't just about quantum; HPC integration is critical. IBM introduced utility-scale dynamic circuits that incorporate classic mid-circuit operations and demonstrated their ability to utilize mid-circuit measurement and feedforward operations. By combining quantum processing with classical control, IBM aims to improve accuracy and reduce gate counts to ultimately realize impactful quantum applications that outperform classical methods – a central tenet for achieving true quantum advantages.