TensorRT Inference Server

TensorRT Inference Server

Logo for TensorRT Inference Server
TensorRT Inference Server provides a data center inference solution optimized for NVIDIA GPUs. It maximizes inference utilization and performance on GPUs via an HTTP or gRPC endpoint, allowing remote clients to request inference for any model that is being managed by the server, as well as providing real-time metrics on latency and requests.
Latest Tag
April 4, 2023
Compressed Size
2.99 GB
Multinode Support
Multi-Arch Support
20.02-py3-clientsdk (Latest) Security Scan Results
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NOTE: TensortRT Inference Server is now called Triton Inference Server.

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What Is The TensorRT Inference Server?

The TensorRT Inference Server provides a cloud inferencing solution optimized for NVIDIA GPUs. The server provides an inference service via an HTTP endpoint, allowing remote clients to request inferencing for any model that is being managed by the server.

Two containers are included: one container provides the TensorRT Inference Server itself and the other container provides client libraries and examples that can be used with the inference server. For more information, refer to TensorRT Inference Server GitHub.

Running The TensorRT Inference Server

Before you can run an NGC deep learning framework container, your Docker environment must support NVIDIA GPUs. To run a container, issue the appropriate command as explained in the Running A Container chapter in the NVIDIA Containers And Frameworks User Guide and specify the registry, repository, and tags. For more information about using NGC, refer to the NGC Container User Guide.

The method implemented in your system depends on the DGX OS version installed (for DGX systems), the specific NGC Cloud Image provided by a Cloud Service Provider, or the software that you have installed in preparation for running NGC containers on TITAN PCs, Quadro PCs, or vGPUs.


  1. Select the Tags tab and locate the container image release that you want to run.

  2. In the Pull Tag column, click the icon to copy the docker pull command.

  3. Open a command prompt and paste the pull command. The pulling of the container image begins. Ensure the pull completes successfully before proceeding to the next step.

  4. Run the container image by following the directions in the TensorRT Inference Server Quick Start Guide.

Suggested Reading

For the latest Release Notes, see the TensorRT Inference Server Release Notes.

For a full list of the supported software and specific versions that come packaged with this framework based on the container image, see the Frameworks Support Matrix.

For more information about the TensorRT Inference Server, see: