Post by qBraid

qBraid is now a first-class cloud target in NVIDIA CUDA-Q. ⚛️ Any CUDA-Q developer can now dispatch to qBraid's backends without leaving their existing workflow. Write your cudaq kernel (or a C++ kernel), set the target to qBraid, and the same code that ran on a simulator now runs on real hardware. A single qBraid API key unlocks the full device lineup: Rigetti, IonQ, IQM, QuEra, and more. Switching devices is just one flag, and it works across both Python and C++. And it's free to start. The default qBraid QIR state-vector simulator lets you sample up to 30 qubits and 2000 shots at no cost, with first submission in under five minutes from install. We've put together starter notebooks that walk through setting the target, sync vs. async submission, and a full cross-vendor QPU benchmarking example: 🔹 Quickstart: https://lnkd.in/g4KJFjXc 🔹 QPU benchmarking: https://lnkd.in/gTXRGM5z Read the full blog 👉 https://lnkd.in/gdt98jwd. Big shoutout to the NVIDIA CUDA-Q community for the support in making this integration happen! #QuantumComputing #CUDAQ #NVIDIA #qBraid #QuantumSoftware #QPU #DeepTech