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/25.08/.

New features

Added functionality

• Multi-node multi-GPU capable SVD, specialized for tall-skinny matrices
• cupynumeric.cross
• cupynumeric.insert
• cupynumeric.logspace
• cupynumeric.real_if_close
• cupynumeric.roots
• cupynumeric.ravel_multi_index
• cupynumeric.copyto
• cupynumeric.diagflat
• cupynumeric.delete
• cupynumeric.nan_to_num
• Support multi-axis reductions

Performance Improvements

• Improve robustness & speed of cupynumeric.sort, by combining allocations where possible, and adding synchronization barriers around NCCL collectives.
• Remove some extraneous blocking that was only necessary to match the behavior of NumPy 1.x.
• Improve performance of NumPy fallback, in particular removing extraneous array copies, and adding special cases for quick fallback to functions such as cupynumeric.concatenate.

Miscellaneous

• Unify all environment variables that control cuPyNumeric's NumPy fallback heuristics, to a single one, CUPYNUMERIC_MAX_EAGER_VOLUME.
• Allow any available BLAS implementation to be used in a source build.

Full Changelog: https://github.com/nv-legate/cupynumeric/compare/v25.07.00...v25.08.00