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NVIDIA Triton Inference Server

developer.nvidia.com

From $375/mo Free plan WindowsLinuxAPISelf-hosted
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Spec score 8.0 #13 of 35 in Deep Learning Software

What it is

NVIDIA Triton Inference Server is open-source software for deploying and serving AI models on GPU- or CPU-based infrastructure. It supports TensorRT, PyTorch, ONNX, OpenVINO, Python and RAPIDS FIL, with model 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. Dynamic batching and concurrent model execution are among its performance features. Requests can use HTTP/REST, gRPC or the C API, with a Java API for in-process use. Triton integrates with Kubernetes for scaling and Prometheus for monitoring. Deployment options include NVIDIA GPUs, other accelerators, x86 and ARM CPUs, cloud, data centers, edge and embedded systems. NVIDIA lists Linux containers for x86 and Arm, plus Windows and Jetson JetPack binaries. Development code and containers are free; production options include a cloud marketplace plan billed pay as you go and a subscription listed at $4,500 a year per GPU. NVIDIA says deployers are responsible for security, and Triton does not sandbox arbitrary model or backend code.

Spec sheet

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.Read 4 Oct 2026 · developer.nvidia.com
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.Read 4 Oct 2026 · developer.nvidia.com
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.Read 4 Oct 2026 · docs.nvidia.com
Headquarters
Santa Clara, California, United StatesRead 28 Sep 2026 · developer.nvidia.com
Founded
1993Read 28 Sep 2026 · developer.nvidia.com
Deployment platforms
It runs on NVIDIA GPUs, non-NVIDIA accelerators, x86 and ARM CPUs, and supports cloud, data center, edge, and embedded deployments.Read 4 Oct 2026 · docs.nvidia.com
Downloads
NVIDIA lists Linux containers for x86 and Arm, plus Windows and Jetson JetPack binary releases on GitHub.Read 4 Oct 2026 · developer.nvidia.com
Enterprise support
NVIDIA AI Enterprise includes Business Standard Support with 24/7 case filing, local business-hours support coverage, a four-hour initial response, and up to three years of long-term branch maintenance for selected components.Read 4 Oct 2026 · docs.nvidia.com
Evaluation
NVIDIA offers a 90-day NVIDIA AI Enterprise evaluation license for Triton production inference.Read 4 Oct 2026 · developer.nvidia.com
Frameworks
Supported frameworks include TensorRT, PyTorch, ONNX, OpenVINO, Python, and RAPIDS FIL.Read 4 Oct 2026 · developer.nvidia.com
Performance features
It offers dynamic batching, concurrent model execution, and optimized configurations.Read 4 Oct 2026 · developer.nvidia.com
Protocols
Inference requests can use HTTP/REST, gRPC, or the C API; Triton also provides a Java API for in-process use cases.Read 4 Oct 2026 · docs.nvidia.com
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.Read 4 Oct 2026 · nvidia.com
Workloads
It supports real-time, batched, ensemble, and audio/video streaming inference workloads.Read 4 Oct 2026 · developer.nvidia.com

Plans and prices

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

Every NVIDIA Triton Inference Server plan and price →

Strong points and limits

Strong points

  • Supports models from six named frameworks
  • Serves real-time, batched and streaming workloads
  • Integrates with Kubernetes and Prometheus
  • Runs on GPUs, accelerators and x86 or ARM CPUs
  • Open-source development option is free

Limits

  • Production subscription is $4,500 a year per GPU
  • Deployers are responsible for solution security
  • Does not sandbox arbitrary model or backend code

Who it suits

Triton suits individuals developing AI inference deployments and enterprises serving models in production. It supports a range of model frameworks, hardware and deployment environments.

Verdict

Triton supports varied inference workloads and deployment targets, with free development options and paid production choices. Production users should account for the stated security responsibilities and limits on sandboxing.

Where Specifiction places it

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