| Sample | Language | Format | Description |
|---|---|---|---|
| sampleOnnxMNIST | C++ | ONNX | “Hello World” For TensorRT With ONNX |
| network_api_pytorch_mnist | Python | INetwork | “Hello World” For TensorRT Using Pytorch |
| Sample | Language | Format | Description |
|---|---|---|---|
| sampleCudla | C++ | INetwork | Using The CuDLA API To Run A TensorRT Engine (aarch64 only) |
| sampleDynamicReshape | C++ | ONNX | Digit Recognition With Dynamic Shapes In TensorRT |
| sampleEditableTimingCache | C++ | INetwork | Create a deterministic build using editable timing cache |
| sampleNamedDimensions | C++ | ONNX | Working with named input dimensions |
| sampleNonZeroPlugin | C++ | INetwork | Adding plugin with data-dependent output shapes |
| sampleIOFormats | C++ | ONNX | Specifying TensorRT I/O Formats |
| sampleProgressMonitor | C++ | ONNX | Progress Monitor API usage |
| engine_refit_onnx_bidaf | Python | ONNX | refitting an engine built from an ONNX model via parsers. |
| introductory_parser_samples | Python | ONNX | Introduction To Importing Models Using TensorRT Parsers |
| onnx_packnet | Python | ONNX | TensorRT Inference Of ONNX Models With Custom Layers |
| simpleProgressMonitor | Python | ONNX | Progress Monitor API usage |
| python_plugin | Python | INetwork/ONNX | Python-based TRT plugins |
| non_zero_plugin | Python | INetwork/ONNX | Python-based TRT plugin for NonZero op |
| sample_plugin_v2_to_v3_migration | Python | INetwork | Migrating a custom plugin from IPluginV2DynamicExt to IPluginV3 |
| cute_dsl_plugin | Python | INetwork | Python-based TRT plugin for RMSNorm with a CuteDSL kernel |
| attention_mdtrt | Python | ONNX | Multi-device attention inference with MPI and NCCL |
Many samples require the TensorRT sample data package. If not already mounted under /usr/src/tensorrt/data (NVIDIA NGC containers), download and extract it:
-
Download the current TensorRT sample data package. Sample data is updated only when needed, so the package may be hosted under an earlier TensorRT release.
wget https://github.com/NVIDIA/TensorRT/releases/download/v11.0/tensorrt_sample_data_20260602.zip
-
Extract and set up the data:
unzip tensorrt_sample_data_*.zip mkdir -p /usr/src/tensorrt/data cp -r tensorrt_sample_data_*/* /usr/src/tensorrt/data/ export TRT_DATADIR=/usr/src/tensorrt/data
After extraction, the data directory structure should be:
$TRT_DATADIR/
├── int8_api/
├── mnist/
└── resnet50/
