This is a beta release of cuPyNumeric.

Pip wheels are available on PyPI at https://pypi.org/project/nvidia-cupynumeric/, for Linux (x86-64 and ARM64, with CUDA and multi-node support) and macOS (for ARM64). Conda packages are available at https://anaconda.org/legate/cupynumeric, for Linux (x86-64 and ARM64, with CUDA and multi-node support). GASNet-based (rather than UCX-based) conda packages are under the gex label. Windows is currently supported through WSL.

Documentation for this release can be found at https://docs.nvidia.com/cupynumeric/25.10/.

Highlights

Added functionality

• Implement cupynumeric.in1d.
• Add DLPack import/export support to cuPyNumeric ndarrays.
• Allow batched input for cupynumeric.linalg.solve.

Performance improvements

• Optimized implementation for the special axis= case of cupynumeric.take.
• Improve heuristics for choosing between batched and unbatched matrix multiplication.
• Improved implementation of cupynumeric.nonzero that uses no additional scratch space.
• Identify special cases of advanced indexing that can be executed faster using cupynumeric.einsum.

Documentation / profiling

• Add a tutorial on using Legate Tasks to extend cuPyNumeric.
• Add a user warning when an operation (e.g. printing to the console) causes a sharded array to be gathered onto a single memory.
• Add sub-boxes to the Legate profiler, showing how long the Python interpreter spends inside cuPyNumeric API calls.

Breaking changes

• Move nightly conda packages to a dedicated channel, -c legate-nightly.

Known issues

• We are aware of hangs occurring under certain platforms and UCC configurations, when using cuSolverMp-backed multi-GPU operations (Cholesky factorization and linear solve). We expect these to be fixed by the 25.11 release, that updates to cuSolverMp 0.7.

Full Changelog: https://github.com/nv-legate/cupynumeric/compare/v25.08.00...v25.10.00