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NVIDIA TensorRT™ is a platform for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high-throughput for deep learning inference applications. TensorRT-based applications perform up to 40x faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and finally deploy to hyperscale data centers, embedded, or automotive product platforms.


TensorRT Download
TensorRT Developer Guide


Official FAQ

TensorRT Developer Guide#FAQs

Common FAQ

You can find answers here for some common questions about using TRT.
Refer to the page TensorRT/CommonFAQ

TRT Accuracy FAQ

If your FP16 result or Int8 result is not as expected, below page may help you fix the accuracy issues.
Refer to the page TensorRT/AccuracyIssues

TRT Performance FAQ

If the performance of doing inference with TRT is not as expected, below page may help you to optimize the performance.
Refer to the page TensorRT/PerfIssues

TRT Int8 Calibration FAQ

Below page will present some FAQs about TRT Int8 Calibration.
Refer to the page TensorRT/Int8CFAQ

TRT Plugin FAQ

Below page will present some FAQs about TRT Plugin.
Refer to the page TensorRT/PluginFAQ

How to fix some Common Errors

If you met some Errors during using TRT, please find from below page for the answer.
Refer to the page TensorRT/CommonErrorFix

How to debug or analyze

Below page will help you debugging your inferencing in some ways.
Refer to the page TensorRT/How2Debug

TRT & YoloV3 FAQ

Refer to the page TensorRT/YoloV3


If you have some question about onnx dynamic shape and onnx Parsing issues, this page might be helpful.
Refer to the page TensorRT/ONNX