A guide to building long-term compounding knowledge infrastructure. See details on GitHub .

Triton Inference Server

Triton Inference Server: NVIDIA's high-performance inference server supporting multiple model formats and deployment options.

Overview

Triton Inference Server (formerly TensorRT Inference Server) is NVIDIA’s production-ready inference server. It supports TensorRT, ONNX, PyTorch and other backends, optimized for GPU acceleration and scalable deployments.

Key features

  • Multiple backend support (TensorRT, ONNX Runtime, PyTorch, OpenVINO, Python, etc.).
  • Dynamic batching, sequence batching, model ensembles and model management APIs.
  • Tools for performance analysis (perf_analyzer, model_analyzer) and examples for deployment.

Use cases

  • Large-scale model serving in data centers and cloud environments.
  • Edge and embedded deployments on NVIDIA Jetson devices.
  • Performance-sensitive applications requiring batching, pipelining and GPU acceleration.

Technical details

  • Exposes HTTP/REST and gRPC inference protocols; provides C, C++, Java and Python client libraries.
  • Supports model repositories, model configuration, and custom backends (C++/Python).
  • Recommended deployment via Docker images; integrations for Kubernetes/Helm are provided.

Comments

Triton Inference Server
Resource Info
Author NVIDIA
Added Date 2025-09-27
Open Source Since 2018-10-04
Tags
Open Source Inference Service