Open QBench is an open-source software framework for defining and executing benchmarks across the quantum-classical stack. It offers support for benchmarks on the:
- hybrid level (quantum-classical workflows)
- high level (quantum algorithms)
- low level (compiled quantum programs)
The framework is supports gate-based quantum computers, photonic systems (boson samplers), and quantum annealers.
Beyond the framework, this package also includes a suite of pre-implemented, high-level quantum application benchmarks. These are specifically crafted to evaluate the performance and fidelity of results on diverse physical quantum devices.
First, create and activate a virtual environment:
uv venv
To install the core dependencies of the package, run:
uv pip install open-qbench
We provide a number of optional dependencies (referred to as "extras") for executing specific benchmarks or for enabling support for various quantum hardware providers.
Available extras include:
- Benchmarks:
VQE,QSVM - Providers:
IBM,AQT
To install specific optional dependencies, specify them in your command. You can specify multiple optionals in a single command. For example, to run the VQE benchmark on an IBM Quantum machine, you would run:
uv pip install "open-qbench[VQE, IBM]"
You can combine any of the available extras as needed.
Note
To install the PT-Series SDK used for running experiments on the ORCA Computing systems, you will need to get access to it through the website at https://sdk.orcacomputing.com/ and install it separately.
The package can also be installed with pip. To install the core dependencies run:
pip install open-qbench
To install with specific optional dependencies (e.g., VQE and IBM):
pip install "open-qbench[VQE,IBM]"
This example shows how to execute a simple application benchmark using a Grover circuit on simulated IBM Quantum hardware (check Installation to see how to enable IBM support).
First define samplers used for collecting distributions.
from qiskit_aer.primitives import SamplerV2 as AerSampler
from qiskit_ibm_runtime import Sampler
from qiskit_ibm_runtime.fake_provider import FakeGeneva
ideal_sampler = AerSampler(default_shots=1000)
backend_sampler = Sampler(FakeGeneva())Then use Open QBench to generate a quantum circuit and create your benchmark by defining input and a function used to calculate fidelity.
from open_qbench import ApplicationBenchmark
from open_qbench.apps.circuits import grover
from open_qbench.core import BenchmarkInput
from open_qbench.fidelities import normalized_fidelity
qc = grover.grover_nq(3, 6)
backend = backend_sampler.backend()
benchmark_input = BenchmarkInput(qc, backend)
ab = ApplicationBenchmark(
backend_sampler,
ideal_sampler,
benchmark_input,
name="Grover_benchmark",
accuracy_measure=normalized_fidelity,
)
ab.run()
print(ab.result)We welcome contributions from the community! Please see CONTRIBUTING.md for a detailed guide.
If you use this software in your research, please cite it as:
@article{openqbench2026,
author={Wojciechowski, Konrad
and Kurowski, Krzysztof
and Slysz, Mateusz
and Pecyna, Tomasz},
title={{Open QBench}: A benchmarking framework for evaluating quantum computing platforms},
journal={Quantum Information Processing},
year={2026},
month={Mar},
day={09},
volume={25},
number={3},
pages={98},
issn={1573-1332},
doi={10.1007/s11128-026-05115-2},
}