Global Quantum Investment Surges to $45 Billion: European Startups Lead Innovation Wave in 2024

April 18, 2025
Global Quantum Investment Surges to $45 Billion: European Startups Lead Innovation Wave in 2024
  • A recent report by QED-C reveals that global government commitments to quantum technologies have surged to nearly $45 billion.

  • In 2024, quantum technologies generated approximately $1.5 billion in revenue, with quantum computing alone contributing over $1 billion.

  • Investment in quantum startups has skyrocketed to $2.6 billion in 2024, reflecting a 58% increase from the previous year as the sector transitions from research to commercialization.

  • Kipu Quantum from Germany is focused on developing tailored quantum algorithms, effectively bridging the gap between hardware providers and end-users.

  • Meanwhile, Quantumz.io in Poland is working on hybrid workflows that integrate classical and quantum computing for enterprise applications.

  • Lastly, Silent Waves from France has developed technology for ultrasensitive signal processing, enhancing readout in quantum systems and driving advancements in quantum computing and sensing.

  • Among these, Oxford Ionics, a UK startup, is at the forefront of trapped-ion quantum computing, utilizing Electronic Qubit Control to facilitate easier scaling with semiconductor techniques.

  • Nu Quantum, also from the UK, is pioneering technology that enables networking between quantum computers, akin to classical networking.

  • European quantum computing startups are increasingly attracting attention from venture capitalists, showcasing a range of innovative companies.

  • Isentroniq from France is tackling infrastructure challenges for scaling qubits by creating advanced wiring systems and 3D architectures for superconducting quantum computers.

  • Qilimanjaro, a Spanish startup, is dedicated to analog quantum computing, focusing on practical applications such as optimization and material simulation.

  • Phasecraft, another UK-based company, specializes in optimizing quantum algorithms specifically for materials science and complex optimization problems.

Summary based on 1 source


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