No. 10 of 36 ·Deep Learning Software

NVIDIA Triton Inference Server

Windows · Linux · Self-hosted · API · paid plans from $375/mo

Freedom report

Two barsScore 6.4

Free tierA free tier is on its own pricing page
Open codeNo open-source code on record
Runs widely2 of 6 device platforms
DocumentedPlans, terms and facts published

NVIDIA Triton Inference Server is ranked #10 of 36 in deep learning software on Freedom251. It runs on API, Linux, Self-hosted, Windows. There is a free plan. A free trial is offered. Paid plans start at $375/mo.

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: Yes
Deployment mode: dedicated
GPU accelerators: Yes
Private deployment: Yes
Supported model formats: TensorRT Plan, ONNX, TensorFlow GraphDef, TensorFlow SavedModel, PyTorch TorchScript, PyTorch 2.0
Batch inference: Yes

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The record

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.
Frameworks: Supported frameworks include TensorRT, PyTorch, ONNX, OpenVINO, Python, and RAPIDS FIL.
Performance features: It offers dynamic batching, concurrent model execution, and optimized configurations.
Workloads: It supports real-time, batched, ensemble, and audio/video streaming inference workloads.
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.
Deployment platforms: It runs on NVIDIA GPUs, non-NVIDIA accelerators, x86 and ARM CPUs, and supports cloud, data center, edge, and embedded deployments.
Protocols: Inference requests can use HTTP/REST, gRPC, or the C API; Triton also provides a Java API for in-process use cases.
Downloads: NVIDIA lists Linux containers for x86 and Arm, plus Windows and Jetson JetPack binary releases on GitHub.
Evaluation: NVIDIA offers a 90-day NVIDIA AI Enterprise evaluation license for Triton production inference.
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.
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.
Founded: 1993
Headquarters: Santa Clara, California, United States
Price from: $375/mo

Where it ranks on Freedom251

Best Deep Learning Software in 2026#10 of 36

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Sources

developer.nvidia.com/dynamo-triton· checked 4 Oct 2026
docs.nvidia.com/deeplearning/triton-inference-server/us· checked 4 Oct 2026
docs.nvidia.com/deeplearning/triton-inference-server/us· checked 4 Oct 2026
nvidia.com/en-us/ai/dynamo-triton/get-started/· checked 4 Oct 2026
docs.nvidia.com/ai-enterprise/planning-resource/licensi· checked 4 Oct 2026