IBM revealed plans to deploy its 520-qubit Quantum Nighthawk r3 processor, which will eventually be linked via l-coupler interconnects to build a system exceeding 1,000 qubits. This next iteration builds on the r2 platform, which leverages high-speed reset technology to generate up to 100,000 samples per second. Partner organizations like Oak Ridge National Laboratory and Algorithmiq have already demonstrated significant speedups using the current hardware for materials science tasks. Over 34 billion circuits have already run on the r2 hardware, showing up to 19-fold performance gains over older machines.
Key points
Modular chip-to-chip interconnects and connected cryogenic modules will enable IBM to sca…: Modular chip-to-chip interconnects and connected cryogenic modules will enable IBM to scale its quantum hardware beyond 1,000 qubits.
Current Nighthawk r2 processors achieve up to 19 times better performance than previous s…: Current Nighthawk r2 processors achieve up to 19 times better performance than previous systems by utilizing high-speed qubit reset technology.
Practical research applications in materials simulation run up to 12 times faster on Nigh…: Practical research applications in materials simulation run up to 12 times faster on Nighthawk r2 than on IBM Quantum Heron hardware.
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IBM Quantum Nighthawk Demonstrates New Levels of Speed and Quality, with Plans to Scale Beyond 1,000 Qubits in 2027
YORKTOWN HEIGHTS, NY, November 11, 2026 — IBM (NYSE: IBM) today announced IBM Quantum Nighthawk r3, its next-generation processor, will be built to accurately execute 10,000 quantum operations across 520 qubits to tackle larger, more complex problems while maintaining the speed and quality demonstrated by the current generation Nighthawk available today.
In 2027, IBM plans to link two Nighthawk r3 processors into a single system with more than 1,000 qubits.
To be at the frontier of quantum computing, industry-relevant applications demand both computational quality and speed. Speed matters because a quantum computer delivers its answer in samples: each run of a quantum circuit returns one result. Applications increasingly require circuits executing thousands of quantum operations on approximately 100 qubits or more, generating millions to billions of samples. Scale and quality enable increasingly complex computations, but speed determines whether these demanding workloads can be completed in practical timeframes and at a reasonable cost.
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