Q.ANT today announced the availability of its next-generation Native Processing Unit, the Q.ANT NPU 2, which uses photonic processing to perform nonlinear mathematics natively in light. The company claims the new processor delivers orders-of-magnitude gains in energy efficiency and performance for artificial intelligence and high-performance computing workloads. By replacing transistor logic with analog computation in light, the NPU 2 enables entirely new classes of applications, including physical AI, advanced robotics, next-generation computer vision, and physics-based simulation.
“Q.ANT offers the industry a new class of processors that enable performance gains beyond the incremental improvements of their digital counterparts — opening the door for superior algorithms that digital circuits cannot reach,” said Dr. Michael Förtsch, CEO of Q.ANT. “For years, AI has raced ahead of our ability to power it — energy became the new frontier. With our NPUs, we’ve changed the equation.”
The announcement comes as AI’s acceleration has reached the physical limits of silicon. Each new generation of GPUs consumes more power and water and produces more heat, with cooling systems accounting for up to 40 percent of total data-center energy. Q.ANT’s photonic architecture fundamentally changes this equation. Light travels faster, generates almost no heat, and can execute complex functions in a single optical step that would require thousands of transistors in a CMOS chip. According to Q.ANT, the NPU 2 delivers up to 30x lower energy use and 50x higher performance for complex AI and HPC workloads.
Q.ANT debuted the NPU 2 at Supercomputing 2025 in St. Louis, where it ran a live image-based AI learning demo powered by the Q.ANT Photonic Algorithm Library (Q.PAL) on its photonic processors. The demo showed how the NPU achieves more accurate results with fewer parameters and fewer operations compared to conventional CPU-based systems, demonstrating real-world photonic acceleration within existing server architectures.
“Photonic computing is scaling much faster than CMOS,” said Förtsch. “What took ten years for digital computing, we’ve just achieved in one year with photonics. The second generation of our Native Processing Unit shows how rapidly this transition is happening and why efficient, light-based computation will drive the next wave of AI and HPC.”
The NPU 2 features an enhanced nonlinear processing core optimized for nonlinear network models that dramatically reduce parameter counts and training depth while improving accuracy for image learning, classification, and physics simulation. It is delivered as a turnkey 19-inch rack-mountable server, the Native Processing Server NPS, which contains multiple NPU 2 units and integrates seamlessly with existing CPUs and GPUs via PCIe and C/C++/Python APIs, making photonic acceleration immediately deployable in HPC and data-center environments.
In practical settings like manufacturing, logistics, and inspection, photonic processors can execute nonlinear neural networks far more efficiently. This allows visual AI to recognize defects, track objects, and optimize inventories with fewer parameters, dramatically reducing energy costs and making computer vision systems economically viable. Photonic processors will also accelerate next-generation AI architectures, such as hybrid models that combine statistical reasoning with physical modeling, advancing domains like drug discovery, materials design, and adaptive optimization.
The Q.ANT servers equipped with NPU 2 processors are available to order now, with customer shipments expected in the first half of 2026. Each system ships as a turnkey, data-center-ready server that integrates seamlessly into existing HPC infrastructures.
