nvidia-cuda-tileiras
TileIR Assembler Package
Decision gist · record as of 2026-08-14
Yes, with conditions. Install if you are building CUDA compilation infrastructure or a machine learning framework that needs portable kernel representation; the package is actively maintained and has no known vulnerabilities. Do not install if you need clear documentation or stable public APIs—it is still in Beta. Verify the license terms before use in proprietary projects, as licensing is currently unclear.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires NVIDIA CUDA runtime libraries (nvidia-cuda-nvcc, nvidia-nvvm, nvidia-nvjitlink) to be installed; platform-specific wheels for Linux (x86_64, aarch64) and Windows (amd64) only.
- Medium install friction due to platform-specific wheels and three NVIDIA CUDA runtime dependencies (nvidia-cuda-nvcc, nvidia-nvvm, nvidia-nvjitlink).
- Package is actively maintained with a recent release cycle.
License · maintenance · safety
(unclear) — License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms before use in proprietary or copyleft-sensitive projects.
last release 2026-05-26 (80 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,497,347 downloads/mo, #3,833 on PyPI
Alternatives
Verify before relying
pip install nvidia-cuda-tileiras
import tileiras
# Use TileIR assembler for kernel compilation- Exact API surface and usage patterns for TileIR intermediate representation
- Whether TileIR is intended for end-user kernel development or primarily for compiler/framework integration
- Documentation availability and maturity level for the assembler interface
What it is and what it does
nvidia-cuda-tileiras is an assembler package that implements TileIR, a language-agnostic intermediate representation designed for CUDA kernels. It sits between high-level kernel code and low-level CUDA compilation, allowing kernels to be expressed and optimized in a portable form independent of the source language or compilation context.
The package depends on three NVIDIA CUDA runtime components and is distributed as platform-specific wheels for Linux and Windows. It targets developers and researchers working on machine learning, deep learning, and scientific computing who need to work with CUDA kernel compilation at an intermediate abstraction level. The package is in Beta status and actively maintained, though its documentation and public API maturity are not yet established.
Use it for
- Compile and optimize CUDA kernels through a portable intermediate representation without language-specific tooling
- Integrate kernel compilation into machine learning frameworks that need cross-platform CUDA support
- Research and develop new CUDA optimization techniques using TileIR as a stable compilation target
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Install if you are building CUDA compilation infrastructure or a machine learning framework that needs portable kernel representation; the package is actively maintained and has no known vulnerabilities. Do not install if you need clear documentation or stable public APIs—it is still in Beta. Verify the license terms before use in proprietary projects, as licensing is currently unclear.
Install
nvidia-cuda-tileiras on PyPI
Before you install
Medium install friction due to platform-specific wheels and three NVIDIA CUDA runtime dependencies (nvidia-cuda-nvcc, nvidia-nvvm, nvidia-nvjitlink). Package is actively maintained with a recent release cycle.
Requires NVIDIA CUDA runtime libraries (nvidia-cuda-nvcc, nvidia-nvvm, nvidia-nvjitlink) to be installed; platform-specific wheels for Linux (x86_64, aarch64) and Windows (amd64) only.
License in practice
License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify licensing terms before use in proprietary or copyleft-sensitive projects.
Quickstart
pip install nvidia-cuda-tileiras
import tileiras
# Use TileIR assembler for kernel compilationVerify before relying
- Exact API surface and usage patterns for TileIR intermediate representation
- Whether TileIR is intended for end-user kernel development or primarily for compiler/framework integration
- Documentation availability and maturity level for the assembler interface
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 3 packagesnvidia-cuda-nvccnvidia-nvvmnvidia-nvjitlink |
| Maintenance | Actively maintained 80 days since the last release |
| First released | |
| Downloads | 1,497,347 / month, #3,833 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchNatural Language :: EnglishOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: MathematicsTopic :: Software DevelopmentTopic :: Software Development :: Libraries |
Evidence: nvidia_cuda_tileiras-13.3.36-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_cuda_tileiras-13.3.36-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; nvidia_cuda_tileiras-13.3.36-py3-none-win_amd64.whl
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See also nvidia-nvvm · tilelang · slangtorch · nvidia-cuda-nvrtc-cu11 · nvidia-cuda-nvcc · nvidia-cuda-nvrtc-cu12 · ailment · nvidia-cuda-nvrtc · nvidia-cuda-nvcc-cu12 · pyvex