aiqbench analysis
The divi pipeline addresses a critical bottleneck in near-term quantum computing by optimizing the submission of thousands of near-identical circuits, achieving up to 148x faster execution compared to established frameworks like PennyLane, Qiskit, and Cirq. By treating batch generation as a composable pipeline while maintaining vendor agnosticism through standard OpenQASM output, divi offers researchers a practical solution to reduce cloud compute costs and accelerate variational algorithm workflows. This benchmark highlights that scaling quantum software now hinges on efficient circuit management rather than solely on increasing qubit counts.
Xanadu’s PennyLane, Qiskit, Cirq Benchmarked Against Divi Pipeline

Running thousands of near-identical quantum circuits is common in useful work on near-term hardware, but current systems often require rebuilding and reserializing each one. This creates a bottleneck before quantum processing unit (QPU) execution, and the article benchmarks a new pipeline, divi, against PennyLane, Qiskit, and Cirq to address this issue.
The challenge of scaling quantum computing isn’t just building more qubits; it’s efficiently managing the thousands of nearly identical circuits required for a single variational step. Qoro has introduced divi, a new software development kit designed to address this bottleneck by treating batch generation as a composable pipeline, achieving up to 148 times faster pipeline execution against frameworks like PennyLane, Qiskit, and Cirq. “Useful work on NISQ hardware rarely means running one circuit; it means thousands of near-identical variants,” the company states, highlighting the scale of the problem, where N_groups × K × T × P circuits fan out from a single optimizer step. Divi maintains vendor agnosticism by outputting standard OpenQASM, offering both speed and flexibility for researchers seeking to optimize cloud compute costs and accelerate results. A single optimizer step in variational quantum algorithms can rapidly multiply the number of…
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