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ORCA launches PT-3 for commercial quantum advantage

Oct. 15, 2026
By AI, Created 07:00 UTC, Oct 15, 2026, AGP -

ORCA Computing has launched PT-3, its newest photonic quantum computer, at Digital Realty’s Innovation Lab in London, where it runs alongside NVIDIA-accelerated computing. The system is already being used for protein design and energy optimization, with ORCA positioning it as a step toward practical commercial quantum advantage.

Why it matters: - ORCA Computing is pitching PT-3 as a practical quantum system for enterprise workloads, not a lab demo. - The system targets AI for science and industrial optimization, two areas where better search and learning could change drug discovery, materials design and energy planning. - PT-3 is designed to work with existing NVIDIA-accelerated infrastructure, which could make adoption easier for companies already using GPUs.

What happened: - ORCA Computing launched PT-3, its newest photonic quantum computer and the first built for commercial quantum advantage. - The first PT-3 system is operating at Digital Realty’s Innovation Lab in London. - PT-3 runs alongside NVIDIA-accelerated computing in the lab. - ORCA said the system is modular, upgradeable in the field, operational within hours of installation and built to scale over time.

The details: - PT-3 operates at room temperature. - The system uses 6 kW across two standard racks. - ORCA said PT-3 improves the expressivity of AI models when paired with GPUs, helping them learn from limited data and identify better candidates for drugs and materials. - ORCA used PT-3 with NVIDIA’s Proteína protein-design model in a hybrid quantum-classical setup trained on 32 NVIDIA Hopper GPUs and a PT-3 using 64 photons in 128 qumodes. - The hybrid model outperformed the classical baseline on designability and improved the ratio of useful proteins by 20%. - The model also generated novel proteins with a different mix of secondary structures. - ORCA said PT-3 is being applied to energy scheduling and other optimization problems. - In a 25,755-variable unit commitment benchmark, PT-3 ran the hybrid workflow in about an hour. - ORCA said that was more than 12 times faster than its predecessor at the same solution quality. - In testing described in the white paper, the hybrid solver matched the solution quality of an industry-standard commercial optimization solver and, with more runtime, found the best solutions of any method tested. - Earlier ORCA work with the Technical University of Denmark using the PT-2 system produced about twice as many strong peptide binders as classical AI, with wet-lab validation. - PT-2 also generated 49% more valid, unique molecules on the QM9 benchmark. - ORCA said it has installed 11 PT Series quantum systems in customer data centers worldwide and works with more than 35 customers and partners. - ORCA was founded in 2019 as a spinout of the University of Oxford and is headquartered in London with an office in Austin.

Between the lines: - The launch frames quantum computing as a hybrid infrastructure play, not a replacement for classical computing. - ORCA’s message is that value comes from combining photonic quantum hardware with GPUs to improve real workloads rather than chase isolated benchmarks. - Digital Realty’s role suggests ORCA wants enterprise customers to see PT-3 in a real data center environment before broader deployment.

What's next: - ORCA said enterprise users can trial PT-3 through Digital Realty for workloads in life sciences, defense, energy and logistics. - Richard Murray and the ORCA team will be available for interviews at NVIDIA GTC Berlin from Oct. 20-22, 2026, at booth 7083 in the Inception showcase. - ORCA said the PT-3 platform will keep improving as customers upgrade the field-deployable system over time.

The bottom line: - ORCA is trying to move quantum computing from promise to production by pairing PT-3 with NVIDIA infrastructure and showing early results in protein design and energy optimization.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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