Full Feature Matrix
| Feature | Qiskit | Cirq | PennyLane | Braket | CUDA-Q |
|---|---|---|---|---|---|
Main Language | Python | Python | Python | Python | Python/C++ |
Local CPU sim | ✓ | ✓ | ✓ | ✓ | ✓ |
GPU simulator CUDA acceleration | ~ (aer-gpu) | ✗ | ~ (lightning) | ✗ | ✓✓ |
Max sim qubits statevector, local | 30+ (CPU) | ~25 | 25+ | 25 local | 34+ (GPU) |
Differentiable autograd/backprop | ~ (partial) | ~ (TF) | ✓✓ | ~ (plugin) | ~ |
QML support | ~ (qiskit-ml) | ✗ | ✓✓ | ~ | ~ |
Built-in VQE/QAOA | ✓ | ~ | ✓ | ~ | ~ |
Noise modeling | ✓✓ | ✓✓ | ✓ | ✓ | ✓ |
Pulse control hardware-level | ✓ | ~ | ✗ | ✗ | ✗ |
HLQuantum support | ✓ | ✓ | ✓ | ✓ | ✓ |
Best for | IBM hardware | Google AI / noise | QML / research | AWS ecosystem | GPU performance |
✓ = full support · ~ = partial/plugin · ✗ = not supported · * = via HLQuantum integration
Which SDK Should I Use?
Based on your primary use case:
First quantum project
Qiskit has the largest community, most tutorials, and free IBM QPU access. It's where most beginners start.
Quantum machine learning
PennyLane is purpose-built for QML — differentiable circuits with PyTorch, JAX, and TensorFlow integration.
Maximum simulation speed
CUDA-Q runs on NVIDIA GPUs and is 100–10,000× faster than CPU simulators for 20+ qubit circuits.
VQE / quantum chemistry
Qiskit Nature + PennyLane both have excellent VQE support. PennyLane's differentiability makes gradient-based optimization easier.
Best gate fidelity QPU
IonQ's trapped-ion systems offer the highest 2-qubit gate fidelities available, with all-to-all qubit connectivity.
AWS / cloud-native workflow
Braket integrates seamlessly with the AWS ecosystem. Supports multiple QPU providers and managed cloud simulators.
Google hardware or noise research
Cirq is purpose-built for NISQ circuits with detailed noise modeling. Direct access to Google Quantum AI hardware (by application).
Run on multiple backends
HLQuantum gives you a single API for all SDKs. Write one circuit, run on any backend with a flag change.
Use all backends from one API
Instead of choosing, use HLQuantum to target Qiskit, Cirq, PennyLane, Braket, CUDA-Q, and IonQ from a single circuit. Switch with a flag — no rewrites.
result = hlq.run(qc, backend="qiskit") # IBM Aer result = hlq.run(qc, backend="cudaq") # NVIDIA GPU result = hlq.run(qc, backend="ionq", device="aria-1") # Real QPU