onnxruntime-ep-nv-tensorrt-rtx
NVIDIA TensorRT RTX Execution Provider plugin for ONNX Runtime.
Enables hardware-accelerated inference on NVIDIA RTX GPUs (Ampere / RTX 30xx and later) via the ORT Plugin EP ABI.
About NVIDIA TensorRT for RTX
NVIDIA® TensorRT™ for RTX (TensorRT-RTX) is an inference optimization library dedicated for deploying AI inference on NVIDIA GeForce RTX GPUs. It is a great choice for developers building applications that must run on Windows or Linux PCs, laptops, or workstations.
This package bundles the TensorRT-RTX runtime libraries alongside the ONNX Runtime EP plugin so that no separate TensorRT-RTX installation is required.
For more information about TensorRT-RTX, visit https://developer.nvidia.com/tensorrt-rtx.
Online documentation: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/index.html
License agreement: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/reference/sla.html
References
- Release Notes: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/getting-started/release-notes.html
- Support Matrix: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/getting-started/support-matrix.html
- Installation Guide: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/installing-tensorrt-rtx/installation-overview.html
- C++ API: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/_static/c-api/index.html
- Python API: https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/_static/python-api/index.html
Requirements
- NVIDIA RTX GPU (Ampere or later)
- NVIDIA GPU driver with CUDA 13 support
pip install onnxruntime>=1.24
Installation
pip install onnxruntime>=1.24
pip install onnxruntime-ep-nv-tensorrt-rtx
Usage
import onnxruntime as ort
import onnxruntime_ep_nv_tensorrt_rtx as trt_ep
# Register the EP plugin
ort.register_execution_provider_library(trt_ep.get_ep_name(), trt_ep.get_library_path())
# List available devices
devices = [d for d in ort.get_ep_devices() if d.ep_name == trt_ep.get_ep_name()]
print(f"TensorRT RTX devices: {len(devices)}")
# Create session with EP
so = ort.SessionOptions()
so.add_provider_for_devices(devices, {})
sess = ort.InferenceSession("model.onnx", sess_options=so)
License
Apache 2.0. See LICENSE.
Metadata
Release files for onnxruntime-ep-nv-tensorrt-rtx-cu13 0.5.0
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| File | Reset | |||
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| onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-win_arm64.whl | Python 3 | none | Windows ARM64 | Details |
| onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-manylinux_2_35_aarch64.whl | Python 3 | none | Linux glibc 2.35+ ARM64 | Details |
| onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-manylinux_2_28_x86_64.whl | Python 3 | none | Linux glibc 2.28+ x86-64 | Details |
Total release size: 490.7 MB
Release files / onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-win_arm64.whl
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| Download URL | onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-win_amd64.whl |
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| Size | 110.9 MB |
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| Size | 134.9 MB |
| Tags | Linux glibc 2.35+ ARM64 Python 3 |
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| Download URL | onnxruntime_ep_nv_tensorrt_rtx_cu13-0.5.0-py3-none-manylinux_2_28_x86_64.whl |
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| Tags | Linux glibc 2.28+ x86-64 Python 3 |
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