TensorRT
NVIDIATensorRT is NVIDIA's SDK for compiling trained networks into optimized inference engines for NVIDIA GPUs, applying layer fusion, kernel selection and explicit quantization. This repository holds the open-source components: the ONNX parser, the plugin library, the Python bindings and samples. The optimizing builder itself ships as a prebuilt binary release that the repository links against.
Verified 2026-08-18 via the GitHub API and the LICENSE body.
Openness
2 high confidence- license
- Apache-2.0(OSI)
- source
- partial
Apache-2.0 license body confirmed. Source is `partial` rather than `public`: the Apache-2.0 license covers the parsers, plugins, bindings and samples in this repository, and the README's build instructions require downloading a prebuilt TensorRT release tarball and pointing TRT_LIBPATH at it, so the optimizing builder that is the product is not in the published tree. The formula settles a partial source on `source` alone, so nothing about the license can lift it.
- https://github.com/NVIDIA/TensorRT/blob/main/LICENSE recorded 2026-08-18
LICENSE file is the verbatim Apache-2.0 text
- https://api.github.com/repos/NVIDIA/TensorRT recorded 2026-08-18
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for NVIDIA/TensorRT.
- https://github.com/NVIDIA/TensorRT/blob/main/README.md recorded 2026-08-18
README's build instructions require downloading a prebuilt TensorRT release tarball from developer.nvidia.com and pointing TRT_LIBPATH at its lib directory, so the optimizing builder is linked as a binary rather than built from this repository, which holds the parsers, plugins, bindings and samples.
Adoption
3 high confidence189,754 PyPI downloads of `tensorrt` in the trailing 30 days, which lands in the 100K-1M band of the software usage scale, level 3.
- https://pypistats.org/api/packages/tensorrt/recent recorded 2026-08-18
last_month downloads = 189,754 for tensorrt
Capability
4 medium confidenceBanded on the category feature matrix as full compilation narrowed to one vendor's targets. Placed one band below the apache-tvm anchor, on a matrix that bands on how much of the model-to-hardware transformation pipeline a product performs, over how many inputs and targets.
- https://github.com/NVIDIA/TensorRT/blob/main/README.md recorded 2026-08-18
README still documents the open source components of the TensorRT SDK, and build instructions that require downloading a prebuilt TensorRT release tarball and setting TRT_LIBPATH.
Verified 2026-08-18