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NVIDIA Triton Inference Server

C
C tier on Deep Learning SoftwareScore 6.8 · #13 of 36
Android app
Not listed
Free plan
Yes
Paid plans from
$375/mo
Runs on
api, Linux, self-hosted, Windows
developer.nvidia.com
The NVIDIA Triton Inference Server homepage
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Summary

NVIDIA Triton Inference Server, part of Dynamo-Triton, is open-source software for deploying and running AI models on GPU- or CPU-based infrastructure. It supports TensorRT, PyTorch, ONNX, OpenVINO, Python, and RAPIDS FIL, with formats including TensorRT Plan, ONNX, TensorFlow GraphDef and SavedModel, PyTorch TorchScript, and PyTorch 2.0. Triton serves real-time, batched, ensemble, and audio/video streaming workloads, with dynamic batching and concurrent model execution. Requests can use HTTP/REST, gRPC, or the C API, and a Java API supports in-process use. It integrates with Kubernetes for scaling and Prometheus for monitoring, and runs on NVIDIA GPUs, other accelerators, and x86 or ARM CPUs across cloud, data center, edge, and embedded deployments. Open-source code and free NGC containers support development. Production options include NVIDIA AI Enterprise, listed at 4500.00 USD per year per GPU for a subscription; cloud marketplace use is pay as you go. NVIDIA says deployers are responsible for security and Triton does not sandbox arbitrary model or backend code.

Who it is for

Triton suits developers deploying inference workloads across supported model frameworks and GPU or CPU infrastructure. NVIDIA positions GitHub and NGC options for individual development and AI Enterprise for enterprise production use.

What is good

  • Open-source development option
  • Supports multiple model frameworks and formats
  • Handles real-time and batched workloads
  • Integrates with Kubernetes and Prometheus
  • Runs on GPU and CPU infrastructure

What to know first

  • Security is the deployer's responsibility
  • Does not sandbox arbitrary model or backend code
  • AI Enterprise subscription costs 4500.00 USD per year per GPU
  • Cloud marketplace production support is limited to 3 calls

Verdict

Triton offers broad deployment and workload support, with open-source development and separate enterprise production options. Production teams should account for the listed licensing choices and take responsibility for securing deployments.

NVIDIA Triton Inference Server plans and pricing

All plans
Open-source development Free Open-source code on GitHub · free Triton containers on NVIDIA NGC for development nvidia.com · 4 Oct 2026
NVIDIA AI Enterprise cloud production $1 Consumption / Pay as you go Cloud marketplace production use · support limited to 3 calls docs.nvidia.com · 4 Oct 2026
NVIDIA AI Enterprise subscription $4,500/yr 1 year; subscription includes support Per GPU · for production use · Business Standard Support included docs.nvidia.com · 4 Oct 2026

Compared on deep learning software

Free plan
Yesdeveloper.nvidia.com
Deployment mode
dedicateddeveloper.nvidia.com
GPU accelerators
Yesdeveloper.nvidia.com
Private deployment
Yesdeveloper.nvidia.com
Supported model formats
TensorRT Plan, ONNX, TensorFlow GraphDef, TensorFlow SavedModel, PyTorch TorchScript, PyTorch 2.0developer.nvidia.com
Batch inference
Yesdeveloper.nvidia.com

Facts

Purpose
Dynamo-Triton is open-source inference-serving software for deploying, running, and scaling AI models from multiple frameworks on GPU- or CPU-based infrastructure.developer.nvidia.com · 4 Oct 2026
Frameworks
Supported frameworks include TensorRT, PyTorch, ONNX, OpenVINO, Python, and RAPIDS FIL.developer.nvidia.com · 4 Oct 2026
Performance features
It offers dynamic batching, concurrent model execution, and optimized configurations.developer.nvidia.com · 4 Oct 2026
Workloads
It supports real-time, batched, ensemble, and audio/video streaming inference workloads.developer.nvidia.com · 4 Oct 2026
Integrations
It integrates with Kubernetes for scaling and Prometheus for monitoring, and NVIDIA lists availability through AWS, Azure, and Google Cloud marketplaces with NVIDIA AI Enterprise.developer.nvidia.com · 4 Oct 2026
Deployment platforms
It runs on NVIDIA GPUs, non-NVIDIA accelerators, x86 and ARM CPUs, and supports cloud, data center, edge, and embedded deployments.docs.nvidia.com · 4 Oct 2026
Protocols
Inference requests can use HTTP/REST, gRPC, or the C API; Triton also provides a Java API for in-process use cases.docs.nvidia.com · 4 Oct 2026
Downloads
NVIDIA lists Linux containers for x86 and Arm, plus Windows and Jetson JetPack binary releases on GitHub.developer.nvidia.com · 4 Oct 2026
Evaluation
NVIDIA offers a 90-day NVIDIA AI Enterprise evaluation license for Triton production inference.developer.nvidia.com · 4 Oct 2026
Security
NVIDIA's secure-deployment guide says solution security is the deployer's responsibility, dynamic model repository updates are disabled by default, and Triton does not sandbox arbitrary model or backend code.docs.nvidia.com · 4 Oct 2026
Who it is for
NVIDIA describes GitHub and NGC options for individuals developing with Triton and NVIDIA AI Enterprise for enterprises purchasing it for production.nvidia.com · 4 Oct 2026

Company

Founded
1993developer.nvidia.com · 28 Sept 2026
Headquarters
Santa Clara, California, United Statesdeveloper.nvidia.com · 28 Sept 2026

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