nvidia-nvtx-cu12
NVIDIA Tools Extension
Decision gist · record as of 2026-08-14
Yes, if you are actively profiling CUDA 12 applications with NVIDIA's Visual Profiler and need fine-grained event annotation. The permissive Apache 2.0 license and zero runtime dependencies make integration straightforward. However, the aging maintenance status (435 days since last release) suggests limited active development—verify that CUDA 12.x is your target version and that the package meets your profiling needs before committing to it.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires CUDA 12.x environment; wheels are platform-specific (Linux x86_64/aarch64, Windows x64 only).
- Medium install friction due to platform-specific wheels (x86_64 Linux, aarch64 Linux, Windows x64 only).
- Maintenance status is aging—last release was 435 days ago—so updates may be infrequent.
License · maintenance · safety
Apache 2.0 (permissive) — Licensed under Apache 2.0 (permissive), allowing broad use, modification, and distribution with minimal restrictions.
last release 2025-06-05 (435 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 24,233,663 downloads/mo, #922 on PyPI
Alternatives
Verify before relying
pip install nvidia-nvtx-cu12
import nvidia.nvtx as nvtx
with nvtx.annotate('operation_name'):
# code to profile- Whether the package works with CUDA versions other than 12.x or if cu12 suffix is strictly required.
- Current maintenance status and whether the 435-day gap since last release indicates active support or dormancy.
What it is and what it does
nvidia-nvtx-cu12 is NVIDIA's Tools Extension library for CUDA 12, providing a C-based annotation API that lets you mark events, code ranges, and resources within your applications. When integrated, these annotations can be captured and visualized using NVIDIA's Visual Profiler, making it easier to identify performance bottlenecks in GPU-accelerated code.
The package is designed for developers working with CUDA-based machine learning, deep learning, and scientific computing workloads. It has no runtime dependencies and supports Python 3.5 through 3.11 on Linux (x86_64 and aarch64) and Windows (x64). The library is particularly useful when you need fine-grained visibility into which parts of your application are consuming GPU resources.
Use it for
- Annotate GPU kernel launches and memory operations to identify performance hotspots in CUDA applications.
- Mark critical sections of deep learning training loops to visualize where time is spent during profiling sessions.
- Instrument custom CUDA code ranges to correlate application logic with GPU activity in Visual Profiler.
- Profile multi-GPU workloads by tagging resource allocation and synchronization points for analysis.
- Debug performance regressions in scientific computing pipelines by capturing timeline events during execution.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are actively profiling CUDA 12 applications with NVIDIA's Visual Profiler and need fine-grained event annotation.
The permissive Apache 2.0 license and zero runtime dependencies make integration straightforward. However, the aging maintenance status (435 days since last release) suggests limited active development—verify that CUDA 12.x is your target version and that the package meets your profiling needs before committing to it.
Install
nvidia-nvtx-cu12 on PyPI
Before you install
Medium install friction due to platform-specific wheels (x86_64 Linux, aarch64 Linux, Windows x64 only). Maintenance status is aging—last release was 435 days ago—so updates may be infrequent.
Requires CUDA 12.x environment; wheels are platform-specific (Linux x86_64/aarch64, Windows x64 only).
License in practice
Licensed under Apache 2.0 (permissive), allowing broad use, modification, and distribution with minimal restrictions.
Quickstart
pip install nvidia-nvtx-cu12
import nvidia.nvtx as nvtx
with nvtx.annotate('operation_name'):
# code to profileVerify before relying
- Whether the package works with CUDA versions other than 12.x or if cu12 suffix is strictly required.
- Current maintenance status and whether the 435-day gap since last release indicates active support or dormancy.
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Aging 435 days since the last release |
| First released | |
| Downloads | 24,233,663 / month, #922 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/ResearchLicense :: Other/Proprietary LicenseNatural 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_nvtx_cu12-12.9.79-py3-none-manylinux1_x86_64.manylinux_2_5_x86_64.whl; nvidia_nvtx_cu12-12.9.79-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_nvtx_cu12-12.9.79-py3-none-win_amd64.whl
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See also nvidia-nvtx · nvidia-nvtx-cu11 · nvtx · nvidia-cuda-cupti-cu12 · nvidia-cuda-cupti-cu11 · cupti-python · nvidia-cuda-cupti · nvidia-cuda-runtime-cu12 · nvidia-cuda-nvcc-cu12 · nvidia-cuda-nvrtc-cu12