.. meta::
   :description: Use Amazon SageMaker managed ML services with AWS Neuron for training and inference on Trainium and Inferentia.
   :keywords: SageMaker, Neuron, JumpStart, HyperPod, training, inference, managed ML, Trainium, Inferentia
   :date-modified: 04/20/2026

.. _deploy-sagemaker:
.. _sagemaker_flow:

Amazon SageMaker
================

Amazon SageMaker is a fully managed machine learning (ML) platform that streamlines the end-to-end ML workflow at scale. AWS Neuron integrates
with Amazon SageMaker to provide optimized performance for ML workloads on AWS Inferentia and AWS Trainium chips.

.. contents:: Table of contents
   :local:
   :depth: 1

SageMaker JumpStart
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Use `Amazon SageMaker JumpStart <https://aws.amazon.com/sagemaker/jumpstart/>`_ to train and deploy models using Neuron. SageMaker JumpStart is an ML hub that accelerates model
selection and deployment. It provides support for fine-tuning and deploying popular models such as Meta's Llama family of models.
Users can customize pre-trained models with their data and easily deploy them.

SageMaker HyperPod
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Use `Amazon SageMaker HyperPod <https://aws.amazon.com/sagemaker/hyperpod/>`_ to streamline ML infrastructure setup and optimization with AWS Neuron. SageMaker HyperPod leverages
pre-configured distributed training libraries to split workloads across numerous AI accelerators, enhancing model performance.
HyperPod ensures uninterrupted training through automatic checkpointing, fault detection, and recovery.

SageMaker Training
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`Amazon SageMaker Model Training <https://aws.amazon.com/sagemaker/train/>`_ reduces the time and cost to train and tune ML models at scale without the need to manage infrastructure.

For a step-by-step guide to training on SageMaker with Trn1 instances, see :doc:`/deploy/sagemaker/training`.

SageMaker Inference
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With `Amazon SageMaker <https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model.html>`_, you can start getting predictions, or inferences, from your trained ML models. SageMaker
provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs.

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   :maxdepth: 1
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   Train on SageMaker </deploy/sagemaker/training>