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Qiskit SDK v2.3

January 2026

• Building on the momentum established across the v2.x series, which has centered on positioning Qiskit as the leading platform for hybrid quantum-HPC workflows, Qiskit SDK v2.3 delivers a significant expansion of the C API alongside faster, more flexible tools for building and optimizing quantum circuits.

  Major updates include:

  • Custom transpiler passes in C - Write custom transpiler passes through Qiskit's C API using the new QkDag object and an expanded QkTarget object, which enable step-by-step inspection, modification, and extension of the compilation process - without rebuilding the entire compiler pipeline.

  • Faster hardware layout selection - Upgrades and Rust-driven performance enhancements to VF2Layout and VF2PostLayout improve the speed and scalability of circuit-to-hardware layout selection, reducing compilation overhead and improving fidelity on quantum hardware.

  • New multi-qubit Pauli measurement - The new PauliProductMeasurement instruction enables joint projective measurement across multiple qubits in a single operation, unlocking compilation to Pauli-based computation - a common representation in fault-tolerant quantum computing.

  • Improvements in early fault-tolerant transpilation - Performance and feature enhancements for transpilation to early fault-tolerant targets - especially Clifford+T targets - help users more efficiently build transpilation pipelines for future QPUs.

  These capabilities give developers greater flexibility to customize quantum circuit optimizations and integrate with existing HPC workflows. Visit the blog for the full technical summary.

Wondering what has changed? Read the changelog and the v2.3 release notes.

To see the release notes for all versions, visit the Qiskit SDK release notes.

April 2026

• Introducing the Executor primitive: We're excited to announce the release of the new Executor primitive and a new version of the noise-learning helper class, NoiseLearnerV3, both of which were first previewed at QDC 2025.

  Together with Samplomatic, they make up the directed execution model, which provides full transparency and control to fine-tune your error mitigation workflow. The Probabilistic error cancellation with shaded lightcones tutorial, for example, demonstrates how this model is used to combine advanced techniques, including shaded lightcones, probabilistic error cancellation (PEC), Twirled Readout Error eXtinction (TREX), and measurement-based postselection, to further improve the result quality.

  If you prefer a higher level of abstraction, EstimatorV2 in Qiskit Runtime continues to provide several built-in error mitigation and suppression techniques, which you can easily tune using the resilience_level option.

  To learn more, see the following guides:

  • Executor quickstart
  • Noise learning helper

  Both of these new features are currently in beta and require qiskit-ibm-runtime version 0.47.0 or higher.

March 2026

• qiskit-ibm-runtime v0.46.0 has been released. View bug fixes and other notes since v0.45.0 in the release notes.

To see the release notes for all versions, visit the IBM Quantum Compute client release notes.