Top 10 Best Quantum AI Software of 2026

PennyLane is an open-source software framework developed by Xanadu for quantum machine learning, differentiable quantum programming, and hybrid quantum-classical computation. It allows users to build, train, and optimize variational quantum circuits using popular machine learning libraries like PyTorch, TensorFlow, JAX, and Keras. PennyLane supports over 30 quantum device plugins, including simulators and real hardware from providers like IBM, Amazon Braket, and Rigetti, enabling seamless workflows from simulation to deployment.

TensorFlow Quantum (TFQ) is an open-source library developed by Google that integrates quantum computing with TensorFlow for hybrid quantum-classical machine learning. It enables users to define quantum circuits using Cirq and incorporate them into TensorFlow models as quantum layers, allowing seamless training of quantum neural networks with classical optimizers. TFQ supports variational quantum algorithms, quantum data encoding, and execution on simulators or real quantum hardware, making it ideal for exploring quantum advantages in AI tasks like classification and optimization.

Qiskit is an open-source quantum computing SDK developed by IBM that enables developers to build, simulate, and execute quantum circuits using Python. It includes modules for quantum algorithms, visualization, and optimization, with extensions like Qiskit Machine Learning for quantum-enhanced AI applications such as variational quantum classifiers and quantum kernel methods. Users can access high-fidelity simulators and real quantum hardware through IBM Quantum, making it a comprehensive platform for Quantum AI research and development.

Cirq is an open-source Python library developed by Google Quantum AI for designing, manipulating, and optimizing quantum circuits, with a focus on Noisy Intermediate Scale Quantum (NISQ) devices and simulators. It enables users to create expressive circuit models, perform simulations, and execute on real quantum hardware like Google's Sycamore processors. Cirq stands out for its low-level control, making it ideal for advanced quantum algorithm development and hardware-aware optimizations.

Strawberry Fields is an open-source Python framework developed by Xanadu for designing, simulating, and executing continuous-variable (CV) photonic quantum circuits. It excels in quantum machine learning and optimization tasks by modeling Gaussian and non-Gaussian operations on photonic hardware. Integrated with PennyLane, it enables hybrid quantum-classical AI workflows, supporting both simulation and cloud-based execution on Xanadu's quantum devices.

PyQuil is Rigetti Computing's open-source Python library designed for quantum programming using the Quil instruction set architecture. It allows users to construct, compile, and execute quantum programs on both high-performance simulators and Rigetti's quantum processing units (QPUs). PyQuil integrates seamlessly with classical Python code, supports parameterized circuits, and provides tools for noise modeling and hybrid quantum-classical workflows, making it suitable for quantum AI applications like variational algorithms.

QuTiP (Quantum Toolbox in Python) is a powerful open-source library for simulating the dynamics of open quantum systems, including master equation solvers, quantum optics, and quantum information processing. It supports a wide range of numerical methods for time evolution, steady-state calculations, and visualization tools like Bloch spheres. While versatile for quantum physics research, it also includes modules for quantum circuits (qip) and pulse control, making it applicable to quantum AI tasks like quantum machine learning prototypes and hybrid simulations.

Microsoft Quantum Development Kit (QDK) is an open-source software development kit for building quantum applications using the domain-specific Q# programming language. It includes high-performance simulators, resource estimation tools, and libraries for quantum algorithms, including support for quantum machine learning and optimization tasks relevant to Quantum AI. QDK integrates seamlessly with Visual Studio, VS Code, and Azure Quantum for access to real quantum hardware from multiple providers.

D-Wave Ocean is an open-source software development kit (SDK) designed for programming D-Wave's quantum annealers, focusing on solving optimization problems via quantum annealing. It includes tools like dwave-binaryc and dwave-networkx for modeling problems as binary quadratic models (BQMs), samplers for local and remote execution, and hybrid solvers that combine quantum and classical computing for larger-scale challenges. Ocean integrates seamlessly with D-Wave's Leap cloud service, providing access to real quantum hardware for practical quantum AI applications in optimization-heavy tasks like machine learning hyperparameters and clustering.

Amazon Braket is a fully managed AWS service providing access to quantum computers and simulators from multiple hardware providers including IonQ, Rigetti, QuEra, and Xanadu. It enables developers to build, test, and run quantum algorithms using frameworks like Qiskit, Cirq, and PennyLane, with support for hybrid quantum-classical workflows. Braket integrates seamlessly with AWS services like SageMaker for scalable quantum machine learning applications.