NVIDIA TensorRT

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On the record

Cloud service access

TensorRT Cloud is available with limited access to select partners, subject to approval.developer.nvidia.com · read 5 Oct 2026

Deployment range

TensorRT targets NVIDIA GPUs in data centers, workstations, laptops, and edge devices.developer.nvidia.com · read 5 Oct 2026

Engine portability

Serialized TensorRT engines are not portable across platforms such as Linux and Windows.docs.nvidia.com · read 5 Oct 2026

Framework integrations

TensorRT integrates with PyTorch and Hugging Face, imports ONNX models, and connects with MATLAB through GPU Coder.developer.nvidia.com · read 5 Oct 2026

Hardware requirement

The support matrix states that TensorRT supports NVIDIA hardware with compute capability SM 7.5 or higher.docs.nvidia.com · read 5 Oct 2026

License limitation

The SDK license says NVIDIA has not tested or certified the SDK for critical applications and places responsibility for applicable legal and regulatory compliance on the user.docs.nvidia.com · read 5 Oct 2026

LLM inference

TensorRT-LLM is an open-source library with a simplified Python API for accelerating and optimizing large language model inference on the NVIDIA AI platform.developer.nvidia.com · read 5 Oct 2026

Optimization

TensorRT optimizes inference with quantization, layer and tensor fusion, and kernel tuning.developer.nvidia.com · read 5 Oct 2026

Purpose

TensorRT is an ecosystem of inference compilers, runtimes, and model optimization tools for high-performance deep learning inference.developer.nvidia.com · read 5 Oct 2026

Security

NVIDIA warns that deserializing an engine from an untrusted source is equivalent to running untrusted native code on the GPU and host.docs.nvidia.com · read 5 Oct 2026

Security guidance

NVIDIA recommends deserializing only engines built by the user or received through a trusted, authenticated channel.docs.nvidia.com · read 5 Oct 2026

Serving

NVIDIA Triton includes TensorRT as a backend and supports dynamic batching, concurrent model execution, model ensembling, and streaming audio and video inputs.developer.nvidia.com · read 5 Oct 2026

Supported precisions

TensorRT Model Optimizer supports FP8, FP4, INT8, INT4, and AWQ techniques.developer.nvidia.com · read 5 Oct 2026

Support resources

NVIDIA provides TensorRT documentation, quick-start guides, sample code, and troubleshooting resources.developer.nvidia.com · read 5 Oct 2026

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