intel-opencl-rt
Intel® oneAPI OpenCL* Runtime
Decision gist · record as of 2026-08-14
Yes, if you are deploying Intel oneAPI OpenCL executables to systems without the full toolkit and your target platform is Windows x86_64 or Linux x86_64 (glibc 2.28+). The package is actively maintained and has no known vulnerabilities. Verify that the proprietary Intel license terms are acceptable for your use case, and ensure the common libraries and licensing packages are also installed.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires the common libraries and common licensing packages in addition to this package; platform-specific wheels limit to Windows x86_64 or Linux x86_64 (glibc 2.28+).
- Medium install friction due to platform-specific wheels (manylinux_2_28_x86_64, win_amd64) and two runtime dependencies (tbb, intel-cmplr-lic-rt).
- Package is actively maintained with recent releases.
License · maintenance · safety
(unclear) — Licensed under Intel End User License Agreement for Developer Tools with unclear treatment. Users should review the proprietary license terms before deployment, particularly in commercial or redistributed contexts.
last release 2026-07-29 (16 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 201,680 downloads/mo, #9,667 on PyPI
Alternatives
Verify before relying
pip install intel-opencl-rt
# Then use OpenCL executables compiled with Intel oneAPI on the target system- Whether the package works on non-x86_64 architectures or older glibc versions
- Exact Python version compatibility (requires_python is unspecified)
- Whether tbb and intel-cmplr-lic-rt are automatically installed or must be manually provided
What it is and what it does
This package is a runtime-only distribution of Intel's OpenCL libraries, designed for deployment scenarios where you need to run OpenCL-compiled executables on machines that do not have the full Intel oneAPI development toolkit installed. It is part of a three-package stack: this package provides the compiler-specific shared libraries, while separate common libraries and common licensing packages provide the broader runtime foundation.
The package is actively maintained (latest release 2026-07-29) and carries two runtime dependencies: tbb and intel-cmplr-lic-rt. Installation is platform-specific, with wheels provided for Windows x86_64 and Linux x86_64 (glibc 2.28+). It is intended for developers, system administrators, and researchers deploying OpenCL workloads in production or research environments.
Use it for
- Deploy OpenCL executables compiled with Intel oneAPI to production servers without installing the full development toolkit
- Distribute containerized OpenCL applications with minimal runtime footprint by including only this package and its dependencies
- Set up OpenCL runtime environments on Linux HPC clusters or Windows compute nodes for scientific computing
- Enable end-user systems to run Intel-compiled OpenCL binaries without requiring development tools
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are deploying Intel oneAPI OpenCL executables to systems without the full toolkit and your target platform is Windows x86_64 or Linux x86_64 (glibc 2.28+).
The package is actively maintained and has no known vulnerabilities. Verify that the proprietary Intel license terms are acceptable for your use case, and ensure the common libraries and licensing packages are also installed.
Install
intel-opencl-rt on PyPI
Before you install
Medium install friction due to platform-specific wheels (manylinux_2_28_x86_64, win_amd64) and two runtime dependencies (tbb, intel-cmplr-lic-rt). Package is actively maintained with recent releases.
Requires the common libraries and common licensing packages in addition to this package; platform-specific wheels limit to Windows x86_64 or Linux x86_64 (glibc 2.28+).
License in practice
Licensed under Intel End User License Agreement for Developer Tools with unclear treatment. Users should review the proprietary license terms before deployment, particularly in commercial or redistributed contexts.
Quickstart
pip install intel-opencl-rt
# Then use OpenCL executables compiled with Intel oneAPI on the target systemVerify before relying
- Whether the package works on non-x86_64 architectures or older glibc versions
- Exact Python version compatibility (requires_python is unspecified)
- Whether tbb and intel-cmplr-lic-rt are automatically installed or must be manually provided
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagestbbintel-cmplr-lic-rt |
| Maintenance | Actively maintained 16 days since the last release |
| First released | |
| Downloads | 201,680 / month, #9,667 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Other AudienceIntended Audience :: Science/ResearchIntended Audience :: System AdministratorsLicense :: Other/Proprietary LicenseOperating System :: Microsoft :: WindowsTopic :: Software Development :: Libraries |
Evidence: intel_opencl_rt-2026.1.1-py2.py3-none-manylinux_2_28_x86_64.whl; intel_opencl_rt-2026.1.1-py2.py3-none-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “opencl runtime deployment”
- intel-opencl-rtProvides Intel OpenCL runtime libraries needed to run OpenCL…
- pyopenclPyOpenCL provides Python bindings to OpenCL, enabling you to write…
- mnnMNN is a lightweight deep learning inference and training framework…
Give your agent the search over MCP, or paste the wish link into any chat.
More Libraries packages
urllib3 is an HTTP client library that provides thread-safe connection pooling, SSL/TLS verification, multipart file uploads, request retries, compression support, and proxy handling for Python applications.
Requests is a Python HTTP library that simplifies sending HTTP/1.1 requests with automatic handling of headers, authentication, cookies, and response parsing.
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
Provides parsing, arithmetic, and recurrence rule computation for dates and times, with timezone support and iCalendar RFC compliance.
Install it if you need to parse flexible date strings, compute relative dates, handle timezones, or work with recurrence rules—it's the de facto choice for these tasks.
Six provides utility functions to write Python code that runs on both Python 2.7 and Python 3.3+, smoothing over language differences between the two versions.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
See also intel-cmplr-lib-rt · intel-sycl-rt · dpcpp-cpp-rt · intel-cmplr-lic-rt · intel-openmp · intel-cmplr-lib-ur · oneccl · mkl · onemkl-license · freeze-core