Quantinuum’s new H2-1 quantum computer proves that trapped-ion architecture, which is well-known for achieving outstanding qubit quality and gate fidelity, is also built for scale – and Quantinuum’s benchmarking team has the data to prove it.
The bottom line: the new System Model H2 surpasses the H1 in complexity and qubit capacity while maintaining all the capabilities and fidelities of the previous generation – an astounding accomplishment when developing successive generations of quantum systems.
The newest entry in the H-Series is starting off with 32 qubits whereas H1 started with 10. H1 underwent several upgrades, ultimately reaching a 20-qubit capacity, and H2 is poised to pick up the torch and run with it. Staying true to the ultimate goal of increasing performance, H2 does not simply increase the qubit count but has already achieved a higher Quantum Volume than any other quantum computer ever built: 216 or 65,536.
Most importantly for the growing number of industrials and academic research institutions using the H-Series, benchmarking data shows that none of these hardware changes reduced the high-performance levels achieved by the System Model H1. That’s a key challenge in scaling quantum computers – preserving performance while adding qubits. The error rate on the fully connected circuits is comparable to the H1, even with a significant increase in qubits. Indeed, H2 exceeds H1 in multiple performance metrics: single-qubit gate error, two-qubit gate error, measurement cross talk and SPAM.
Key to the engineering advances made in the second-generation H-Series quantum computer are reductions in the physical resources required per qubit. To get the most out of the quantum charge-coupled device (QCCD) architecture, which the H-Series is built on, the hardware team at Quantinuum introduced a series of component innovations, to eliminate some performance limitations of the first generation in areas such as ion-loading, voltage sources, and delivering high-precision radio signals to control and manipulate ions.
The research paper, “A Race Track Trapped-Ion Quantum Processor,” details all of these engineering advances, and exactly what impacts they have on the computing performance of the machine. The paper includes results from component and system-level benchmarking tests that document the new machine’s capabilities at launch. These benchmarking metrics, combined with the company’s advances in topological qubits, represent a new phase of quantum computing.
In addition to the expanded capabilities, the new design provides operational efficiencies and a clear growth path.
At launch, H2’s operations can still be emulated classically. However, Quantinuum released H2 at a small percentage of its full capacity. This new machine has the ability to upgrade to more qubits and gate zones, pushing it past the level where classical computers can hope to keep up.
This new generation quantum processor represents the first major trap upgrade in the H-Series. One of the most significant changes is the new oval (or racetrack) shape of the ion trap itself, which allows for a more efficient use of space and electrical control signals.
One key engineering challenge presented by this new design was the ability to route signals beneath the top metal layer of the trap. The hardware team addressed this by using radiofrequency (RF) tunnels. These tunnels allow inner and outer voltage electrodes to be implemented without being directly connected on the top surface of the trap, which is the key to making truly two-dimensional traps that will greatly increase the computational speed of these machines.
The new trap also features voltage “broadcasting,” which saves control signals by tying multiple DC electrodes within the trap to the same external signal. This is accomplished in “conveyor belt” regions on each side of the trap where ions are stored, improving electrode control efficiency by requiring only three voltage signals for 20 wells on each side of the trap.
The other significant component of H2 is the Magneto Optical Trap (MOT) which replaces the effusive atomic oven that H1 used. The MOT reduces the startup time for H2 by cooling the neutral atoms before shooting them at the trap, which will be crucial for very large machines that use large numbers of qubits.
Quantinuum has always valued transparency and supported its performance claims with publicly available data.
To quantify the impact of these hardware and design improvements, Quantinuum ran 15 tests that measured component operations, overall system performance and application performance. The complete results from the tests are included in the new research paper.
The hardware team ran four system-level benchmark tests that included more complex, multi-qubit circuits to give a broader picture of overall performance. These tests were:
H2 showed state-of-the-art performance on each of these system-level tests, but the results of the GHZ test were particularly impressive. The verification of the globally entangled GHZ state requires a relatively high fidelity, which becomes harder and harder to achieve with larger numbers of qubits.
With H2’s 32 qubits and precision control of the environment in the ion trap, Quantinuum researchers were able to achieve an entangled state of 32 qubits with a fidelity of 82.0(7)%, setting a new world record.
In addition to the system level tests, the Quantinuum hardware team ran these component benchmark tests:
The paper includes results from those tests as well as results from these application benchmarks:
Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents.
If we are to create ‘next-gen’ AI that takes full advantage of the power of quantum computers, we need to start with quantum native transformers. Today we announce yet again that Quantinuum continues to lead by demonstrating concrete progress — advancing from theoretical models to real quantum deployment.
The future of AI won't be built on yesterday’s tech. If we're serious about creating next-generation AI that unlocks the full promise of quantum computing, then we must build quantum-native models—designed for quantum, from the ground up.
Around this time last year, we introduced Quixer, a state-of-the-art quantum-native transformer. Today, we’re thrilled to announce a major milestone: one year on, Quixer is now running natively on quantum hardware.
This marks a turning point for the industry: realizing quantum-native AI opens a world of possibilities.
Classical transformers revolutionized AI. They power everything from ChatGPT to real-time translation, computer vision, drug discovery, and algorithmic trading. Now, Quixer sets the stage for a similar leap — but for quantum-native computation. Because quantum computers differ fundamentally from classical computers, we expect a whole new host of valuable applications to emerge.
Achieving that future requires models that are efficient, scalable, and actually run on today’s quantum hardware.
That’s what we’ve built.
Until Quixer, quantum transformers were the result of a brute force “copy-paste” approach: taking the math from a classical model and putting it onto a quantum circuit. However, this approach does not account for the considerable differences between quantum and classical architectures, leading to substantial resource requirements.
Quixer is different: it’s not a translation – it's an innovation.
With Quixer, our team introduced an explicitly quantum transformer, built from the ground up using quantum algorithmic primitives. Because Quixer is tailored for quantum circuits, it's more resource efficient than most competing approaches.
As quantum computing advances toward fault tolerance, Quixer is built to scale with it.
We’ve already deployed Quixer on real-world data: genomic sequence analysis, a high-impact classification task in biotech. We're happy to report that its performance is already approaching that of classical models, even in this first implementation.
This is just the beginning.
Looking ahead, we’ll explore using Quixer anywhere classical transformers have proven to be useful; such as language modeling, image classification, quantum chemistry, and beyond. More excitingly, we expect use cases to emerge that are quantum-specific, impossible on classical hardware.
This milestone isn’t just about one model. It’s a signal that the quantum AI era has begun, and that Quantinuum is leading the charge with real results, not empty hype.
Stay tuned. The revolution is only getting started.
Our team is participating in ISC High Performance 2025 (ISC 2025) from June 10-13 in Hamburg, Germany!
As quantum computing accelerates, so does the urgency to integrate its capabilities into today’s high-performance computing (HPC) and AI environments. At ISC 2025, meet the Quantinuum team to learn how the highest performing quantum systems on the market, combined with advanced software and powerful collaborations, are helping organizations take the next step in their compute strategy.
Quantinuum is leading the industry across every major vector: performance, hybrid integration, scientific innovation, global collaboration and ease of access.
From June 10–13, in Hamburg, Germany, visit us at Booth B40 in the Exhibition Hall or attend one of our technical talks to explore how our quantum technologies are pushing the boundaries of what’s possible across HPC.
Throughout ISC, our team will present on the most important topics in HPC and quantum computing integration—from near-term hybrid use cases to hardware innovations and future roadmaps.
Multicore World Networking Event
H1 x CUDA-Q Demonstration
HPC Solutions Forum
Whether you're exploring hybrid solutions today or planning for large-scale quantum deployment tomorrow, ISC 2025 is the place to begin the conversation.
We look forward to seeing you in Hamburg!
Quantinuum has once again raised the bar—setting a record in teleportation, and advancing our leadership in the race toward universal fault-tolerant quantum computing.
Last year, we published a paper in Science demonstrating the first-ever fault-tolerant teleportation of a logical qubit. At the time, we outlined how crucial teleportation is to realize large-scale fault tolerant quantum computers. Given the high degree of system performance and capabilities required to run the protocol (e.g., multiple qubits, high-fidelity state-preparation, entangling operations, mid-circuit measurement, etc.), teleportation is recognized as an excellent measure of system maturity.
Today we’re building on last year’s breakthrough, having recently achieved a record logical teleportation fidelity of 99.82% – up from 97.5% in last year’s result. What’s more, our logical qubit teleportation fidelity now exceeds our physical qubit teleportation fidelity, passing the break-even point that establishes our H2 system as the gold standard for complex quantum operations.
This progress reflects the strength and flexibility of our Quantum Charge Coupled Device (QCCD) architecture. The native high fidelity of our QCCD architecture enables us to perform highly complex demonstrations like this that nobody else has yet to match. Further, our ability to perform conditional logic and real-time decoding was crucial for implementing the Steane error correction code used in this work, and our all-to-all connectivity was essential for performing the high-fidelity transversal gates that drove the protocol.
Teleportation schemes like this allow us to “trade space for time,” meaning that we can do quantum error correction more quickly, reducing our time to solution. Additionally, teleportation enables long-range communication during logical computation, which translates to higher connectivity in logical algorithms, improving computational power.
This demonstration underscores our ongoing commitment to reducing logical error rates, which is critical for realizing the promise of quantum computing. Quantinuum continues to lead in quantum hardware performance, algorithms, and error correction—and we’ll extend our leadership come the launch of our next generation system, Helios, in just a matter of months.