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This is a preview build of IBM Quantum® documentation. Refer to quantum.cloud.ibm.com/docs for the official documentation.

Introduction to IBM Quantum

In addition to the open-source tools of the Qiskit SDK, Qiskit addons, and other tools that integrate QPUs into compute environments, IBM Quantum® offers several services for quantum computation. This page provides an overview of these services and links to get started working with them.


IBM Quantum Compute Service

IBM Quantum Compute Service, formerly called the Qiskit Runtime Service, is the cloud-based service for executing quantum computations on IBM Quantum hardware. The qiskit-ibm-runtime package is a client for that service, and is the successor to the Qiskit IBM Provider. Quantum Compute streamlines quantum computations and provides optimal implementations of the Qiskit primitive base classes for IBM Quantum hardware. To get started with IBM Quantum primitives, visit the documentation.

Quantum Compute is designed to use additional classical and quantum compute resources, including techniques such as error suppression and error mitigation, to return a higher-quality result from executing quantum circuits on quantum processors. Examples include dynamical decoupling for error suppression, and readout mitigation and zero-noise extrapolation (ZNE) for error mitigation. Learn how to configure these options on the Configure error mitigation page.

Quantum Compute also includes three types of execution modes for running your quantum program on IBM® hardware: Job, Session, and Batch, each of which have different use cases and implications for the quantum job queue. A Job is a single query to a primitive that can be run over a specified number of shots. Sessions allow you to efficiently run multiple jobs in iterative workloads on quantum computers. Batch mode allows you to submit all your jobs at once for parallel processing. Note that Open Plan users cannot submit session jobs.

To quickly install the IBM Quantum Compute client, run the following command:

pip install qiskit-ibm-runtime

See the installation page to set up a development environment for building quantum programs.

Is Quantum Compute open-source?

The short answer is, not all of it. The software that handles the technicalities of running your quantum program on an IBM Quantum device (including any error mitigation and suppression) is not open-source. However, the client software library qiskit-ibm-runtime (which is the interface for users to access IBM Quantum Compute Service), the Qiskit SDK running on the server side, and some of the software used for error mitigation, are open-source. To get involved with Qiskit open-source efforts, visit our GitHub organization at github.com/Qiskit and github.com/Qiskit-Extensions.


IBM Quantum Platform

IBM Quantum Platform provides a unified environment for managing users and organizations, configuring access plans, viewing and organizing workloads submitted to Quantum Compute, and monitoring system activity. Designed to support teams ranging from individual researchers to enterprise-scale programs, the platform centralizes access to the IBM fleet of quantum processing units (QPUs) and associated services. Administrators can manage memberships and permissions, configure entitlements, and oversee usage, while developers benefit from a consistent interface for interacting with quantum systems.

To run quantum jobs, users create an instance within the platform. Each instance provides its own Cloud Resource Name (CRN), which is required for submitting workloads to available QPUs. Once configured, users can select or adjust access plans, track job execution, analyze logs, and integrate the platform seamlessly into their development workflows. Together, these capabilities make IBM Quantum Platform the control center for QPU access and quantum application execution.

For more details, read the setup documentation for getting started with IBM Quantum Platform.


IBM Quantum Functions

IBM Quantum Functions run classical and quantum work as a managed service on IBM Quantum Platform. Choose a pre-built function from the Functions Catalog, or run your own code as a managed workflow.

IBM Quantum Functions Catalog

The IBM Quantum Functions Catalog (qiskit-ibm-catalog.QiskitFunctionsCatalog) offers pre-built services from IBM and partners, designed to accelerate algorithm discovery and application prototyping. Explore the Functions Catalog, including:

  • Circuit functions: Services that include transpilation, error suppression, error mitigation, and post-processing techniques that take abstract circuits and desired measurement observables as input. With Circuit functions, users can discover new algorithms and applications without needing to manage transpilation or quantum hardware performance.
  • Application functions: Services that include entire quantum workflows, from mapping classical to quantum, optimizing for hardware, execution on hardware, and post-processing. Users can prototype industry applications with domain-familiar inputs and outputs.

Find a function by research area

To compare all available functions side by side, see the Introduction to IBM Quantum Functions.

Run a Catalog Function

Premium Plan, Flex Plan, and On-Prem (via IBM Quantum Platform API) Plan members can access IBM-provided functions right away, or purchase licenses for the partner-provided functions directly from those partners.

  1. Set up access to IBM Quantum Functions on your instance.
  2. Follow the function's getting-started guide, or try a tutorial.

The catalog can be installed with pip:

pip install qiskit-ibm-catalog

Managed workflows

Creating utility-scale quantum applications generally requires a variety of compute resource requirements. Managed workflows run your own Python code on classical compute that IBM Quantum Platform manages for you, alongside the quantum hardware. Functions also manages the environment: it sets up storage, and installs and pre-compiles all packages before your job starts. Use a managed workflow to:

  • Persist long-running workloads in the cloud, even if your laptop is turned off
  • Use large-memory and GPU nodes by choosing a compute profile
  • Parallelize classical tasks, such as pre-processing and post-processing
  • Deploy reusable programs in the cloud

To get started, see Managed workflows.