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CUDA-Q Releases
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**latest**

The latest version of CUDA-Q is on the main branch of our `GitHub repository <https://github.com/NVIDIA/cuda-quantum>`__ and is also available as a Docker image. More information about installing the nightly builds can be found :doc:`here <using/install/install>`

- `Docker image (nightly builds) <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nightly/containers/cuda-quantum>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/latest>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/main/docs/sphinx/examples>`__

**0.7.0**

The 0.7.0 release adds support for using :doc:`NVIDIA Quantum Cloud <using/backends/nvqc>`,
giving you access to our most powerful GPU-accelerated simulators even if you don't have an NVIDIA GPU.
With 0.7.0, we have furthermore greatly increased expressiveness of the Python and C++ language frontends. 
Check out our `documentation <https://nvidia.github.io/cuda-quantum/latest/using/quick_start.html>`__ 
to get started with the new Python syntax support we have added, and `follow our blog <https://developer.nvidia.com/cuda-q>`__
to learn more about the new setup and its performance benefits.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum>`__
- `Python wheel <https://pypi.org/project/cuda-quantum/>`__
- `C++ installer <https://github.com/NVIDIA/cuda-quantum/releases>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.7.0>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/releases/v0.7.0/docs/sphinx/examples>`__

The full change log can be found `here <https://github.com/NVIDIA/cuda-quantum/releases>`__.

**0.6.0**

The 0.6.0 release contains improved support for various HPC scenarios. We have added a
:ref:`plugin infrastructure <distributed-computing-with-mpi>` for connecting CUDA-Q 
with an existing MPI installation, and we've added a :ref:`new platform target <remote-mqpu-platform>` that distributes workloads across multiple virtual QPUs, 
each simulated by one or more GPUs.

Starting with 0.6.0, we are now also distributing 
:ref:`pre-built binaries <install-prebuilt-binaries>` for using CUDA-Q with C++.
The binaries are built against the `GNU C library <https://www.gnu.org/software/libc/>`__ 
version 2.28.
We've added a detailed :doc:`Building from Source <using/install/data_center_install>` guide to build these binaries for older `glibc` versions.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum/tags>`__
- `Python wheel <https://pypi.org/project/cuda-quantum/0.6.0>`__
- `C++ installer <https://github.com/NVIDIA/cuda-quantum/releases/0.6.0>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.6.0>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/releases/v0.6.0/docs/sphinx/examples>`__

The full change log can be found `here <https://github.com/NVIDIA/cuda-quantum/releases/0.6.0>`__.

**0.5.0**

With 0.5.0 we have added support for quantum kernel execution on OQC and IQM backends. For more information, see :doc:`using/backends/hardware`.
CUDA-Q now allows to executing adaptive quantum kernels on quantum hardware backends that support it.
The 0.5.0 release furthermore improves the tensor network simulation tools and adds a matrix product state simulator, see :doc:`using/backends/simulators`.

Additionally, we are now publishing images for experimental features, which currently includes improved Python language support.
Please take a look at :doc:`using/install/install` for more information about how to obtain them.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum/tags>`__
- `Python wheel <https://pypi.org/project/cuda-quantum/0.5.0>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.5.0>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/releases/v0.5.0/docs/sphinx/examples>`__

The full change log can be found `here <https://github.com/NVIDIA/cuda-quantum/releases/0.5.0>`__.

**0.4.1**

The 0.4.1 release adds support for ARM processors in the form of multi-platform Docker images and `aarch64` Python wheels. Additionally, all GPU-based backends are now included in the Python wheels as well as in the Docker image.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum/tags>`__
- `Python wheel <https://pypi.org/project/cuda-quantum/0.4.1>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.4.1>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/releases/v0.4.1/docs/sphinx/examples>`__

The full change log can be found `here <https://github.com/NVIDIA/cuda-quantum/releases/0.4.1>`__.

**0.4.0**

CUDA-Q is now available on PyPI!
The 0.4.0 release adds support for quantum kernel execution on Quantinuum and IonQ backends. For more information, see :doc:`using/backends/hardware`.

The 0.4.0 PyPI release does not yet include all of the GPU-based backends.
The fully featured version is available as a Docker image for `linux/amd64` platforms.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum/tags>`__
- `Python wheel <https://pypi.org/project/cuda-quantum/0.4.0>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.4.0>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/0.4.0/docs/sphinx/examples>`__

The full change log can be found `here <https://github.com/NVIDIA/cuda-quantum/releases/tag/0.4.0>`__.

**0.3.0**

The 0.3.0 release of CUDA-Q is available as a Docker image for `linux/amd64` platforms.

- `Docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum/tags>`__
- `Documentation <https://nvidia.github.io/cuda-quantum/0.3.0>`__
- `Examples <https://github.com/NVIDIA/cuda-quantum/tree/0.3.0/docs/sphinx/examples>`__