NVIDIA Triton Inference Server vs. Ray Comparison


NVIDIA Triton Inference Server NVIDIA	Ray Anyscale	+	+
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About NVIDIA Triton™ inference server delivers fast and scalable AI in production. Open-source inference serving software, Triton inference server streamlines AI inference by enabling teams deploy trained AI models from any framework (TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, custom and more on any GPU- or CPU-based infrastructure (cloud, data center, or edge). Triton runs models concurrently on GPUs to maximize throughput and utilization, supports x86 and ARM CPU-based inferencing, and offers features like dynamic batching, model analyzer, model ensemble, and audio streaming. Triton helps developers deliver high-performance inference aTriton integrates with Kubernetes for orchestration and scaling, exports Prometheus metrics for monitoring, supports live model updates, and can be used in all major public cloud machine learning (ML) and managed Kubernetes platforms. Triton helps standardize model deployment in production.	About Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Developers and companies searching for an inference server solution to improve AI production	Audience ML and AI Engineers, Software Developers
Support Phone Support Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing Free Open source. Consumption-based. Free Version Supported Free Trial Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information NVIDIA United States developer.nvidia.com/nvidia-triton-inference-server	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives Modular	Alternatives Anyscale
NVIDIA NIM NVIDIA	Horovod
FauxPilot	Determined AI
NVIDIA TensorRT NVIDIA	Neuralhub
Amazon EC2 Inf1 Instances Amazon View All	Automaton AI View All
Categories AI Inference Supported AI Infrastructure Supported Artificial Intelligence Supported Machine Learning Supported ML Model Deployment Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Amazon EKS Supported Amazon SageMaker Supported Azure Kubernetes Service (AKS) Supported Google Kubernetes Engine (GKE) Supported Kubernetes Supported PyTorch Supported TensorFlow Supported Amazon EC2 Trn2 Instances Not Supported Amazon Elastic Container Service (Amazon ECS) Supported Amazon Web Services (AWS) Not Supported Anyscale Not Supported Azure Machine Learning Supported FauxPilot Supported Flyte Not Supported Gemini Enterprise Agent Platform Supported Google Cloud Platform Not Supported HPE Ezmeral Supported MXNet Supported Thunder Compute Supported io.net Not Supported Show More Integrations View All 20 Integrations	Integrations Amazon EKS Supported Amazon SageMaker Supported Azure Kubernetes Service (AKS) Supported Google Kubernetes Engine (GKE) Supported Kubernetes Supported PyTorch Supported TensorFlow Supported Amazon EC2 Trn2 Instances Supported Amazon Elastic Container Service (Amazon ECS) Not Supported Amazon Web Services (AWS) Supported Anyscale Supported Azure Machine Learning Not Supported FauxPilot Not Supported Flyte Supported Gemini Enterprise Agent Platform Not Supported Google Cloud Platform Supported HPE Ezmeral Not Supported MXNet Not Supported Thunder Compute Not Supported io.net Supported Show More Integrations View All 22 Integrations
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