AWS Instance Types

AWS EC2 Instance Types Grouped by Family

General-Purpose

1. M1 (e.g., m1.small, m1.medium, m1.large)
   • Balanced CPU, memory, and network resources
   • Suitable for small to medium-sized databases, data processing, caching, and backend servers for SAP, Microsoft SharePoint, and other enterprise applications
2. M3 (e.g., m3.large, m3.xlarge, m3.2xlarge)
   • Higher CPU performance and larger instance sizes
   • Recommended for general-purpose instances with demanding CPU requirements
3. M6g (e.g., m6g.medium, m6g.large, m6g.xlarge, m6g.2xlarge)
   • Latest generation of general-purpose instances
   • Provides a balance of CPU, memory, and network resources
   • Suitable for small to medium-sized databases, data processing, caching, and backend servers for SAP, Microsoft SharePoint, and other enterprise applications

Compute-Optimized

1. C1 (e.g., c1.xlarge, c1.2xlarge, c1.4xlarge)
   • High CPU-to-memory ratio
   • Ideal for CPU-bound scale-out applications, such as front-end fleets for high-traffic web sites, on-demand batch processing, distributed analytics, web servers, video encoding, and high-performance science and engineering applications
2. CC2 (e.g., cc2.8xlarge)
   • Latest generation of compute-optimized instances
   • Provides the lowest cost for CPU performance among all EC2 instance types
   • Supports cluster networking and high core count (32 vCPUs)

Memory-Optimized

1. M2 (e.g., m2.xlarge, m2.2xlarge, m2.4xlarge)
   • High memory-to-CPU ratio
   • Suitable for memory-bound applications, such as high-performance databases, distributed cache, genome assembly, and larger deployments of SAP, Microsoft SharePoint, and other enterprise applications
2. CR1 (e.g., cr1.16xlarge)
   • Latest generation of memory-optimized instances
   • Provides more memory (244 GiB), faster CPU (Intel Xeon E5-2670), and supports cluster networking

Storage-Optimized

1. HI1 (e.g., hi1.4xlarge)
   • Optimized for very high random I/O performance and low cost per IOPS
   • Ideal for transactional applications, such as large deployments of NoSQL databases like Cassandra and MongoDB
2. HS1 (e.g., hs1.8xlarge)
   • Optimized for very high storage density, low storage cost, and high sequential I/O performance
   • Suitable for large-scale data warehouses, large always-on Hadoop clusters, and cluster file systems

GPU Instances

1. CG1 (e.g., cg1.4xlarge)
   • High-performance computing instances with NVIDIA Tesla V100 GPUs
   • Suitable for applications that require intense graphics processing, such as video encoding, scientific simulations, and machine learning

Micro Instances

1. T1 (e.g., t1.micro)
   • Very low-cost instance option with a small amount of CPU resources
   • May opportunistically increase CPU capacity in short bursts when additional cycles are available
   • Suitable for lower-throughput applications, such as bastion hosts or administrative applications, or for low-traffic websites that require additional compute cycles from time to time

AWS Instance Types for High-Throughput

AWS instance types support high-throughput workloads like video transcoding and scientific simulations through various combinations of CPU, memory, storage, and networking capacity. Here are some key features and instance types that cater to these workloads:

• Compute-Optimized Instances: M5zn, C6g, C6gn, and Hpc6id instances are designed for applications that require extremely high single-thread performance and high throughput, such as:
  • Gaming
  • High Performance Computing (HPC)
  • Simulation modeling for industries like automotive, aerospace, energy, and telecommunications
• Storage-Optimized Instances: I3en, H1, and I2 instances are ideal for big data processing clusters, MapReduce workloads, and distributed file systems, making them suitable for:
  • Batch processing workloads
  • Media transcoding
  • High-performance web servers
  • Scientific modeling
• High-Performance Computing (HPC) Instances: Hpc6a and Hpc6id instances are designed for tight-coupled, compute-intensive, and high-performance computing jobs, including:
  • Computational fluid dynamics
  • Weather forecasting
  • Molecular dynamics
  • Complex simulations and deep learning workloads
• GPU-Powered Instances: Vt1 instances, powered by NVIDIA V100 or T4 GPUs, are optimized for:
  • Live transcoding video at up to 4K UHD resolutions
  • Machine learning inference
  • Graphics rendering
  • Scientific simulations
• Network-Optimized Instances: R instances, with Enhanced Networking and EBS optimization, are suitable for workloads that require high networking throughput, such as:
  • High-performance file systems
  • Distributed web scale in-memory caches
  • Real-time big data analytics
  • Telco applications like 5G User Plane Function (UPF)

AWS instance types offer a range of configurations to support high-throughput workloads, allowing you to choose the optimal instance for your specific needs. By leveraging these instance types, you can efficiently run demanding workloads like video transcoding and scientific simulations in the cloud.

AWS Instance Types from AWS DOCS

When you launch an instance, the instance type that you specify determines the hardware of the host computer used for your instance. Each instance type offers different compute, memory, and storage capabilities, and is grouped in an instance family based on these capabilities. Select an instance type based on the requirements of the application or software that you plan to run on your instance. For more information about features and use cases, see Amazon EC2 Instance Types Details.

Amazon EC2 dedicates some resources of the host computer, such as CPU, memory, and instance storage, to a particular instance. Amazon EC2 shares other resources of the host computer, such as the network and the disk subsystem, among instances. If each instance on a host computer tries to use as much of one of these shared resources as possible, each receives an equal share of that resource. However, when a resource is underused, an instance can consume a higher share of that resource while it’s available.

Each instance type provides higher or lower minimum performance from a shared resource. For example, instance types with high I/O performance have a larger allocation of shared resources. Allocating a larger share of shared resources also reduces the variance of I/O performance. For most applications, moderate I/O performance is more than enough. However, for applications that require greater or more consistent I/O performance, consider an instance type with higher I/O performance.

Contents

• Available instance types
• Hardware specifications
• Hypervisor type
• AMI virtualization types
• Processors
• Find an Amazon EC2 instance type
• Get recommendations from EC2 instance type finder
• Get EC2 instance recommendations from Compute Optimizer
• Amazon EC2 instance type changes
• Burstable performance instances
• Performance acceleration with GPU instances
• Amazon EC2 Mac instances
• Amazon EBS-optimized instance types
• CPU options for Amazon EC2 instances
• AMD SEV-SNP for Amazon EC2 instances
• Processor state control for Amazon EC2 Linux instances

Available instance types

Amazon EC2 provides a wide selection of instance types optimized to fit different use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity and give you the flexibility to choose the appropriate mix of resources for your applications. Each instance type includes one or more instance sizes, allowing you to scale your resources to the requirements of your target workload.

Instance type naming conventions

Names are based on instance family, generation, processor family, capabilities, and size. For more information, see Naming conventions in the Amazon EC2 Instance Types Guide.

Find an instance type

To determine which instance types meet your requirements, such as supported Regions, compute resources, or storage resources, see Find an Amazon EC2 instance type and Amazon EC2 instance type specifications in the Amazon EC2 Instance Types Guide.

Hardware specifications

For detailed instance type specifications, see Specifications in the Amazon EC2 Instance Types Guide. For pricing information, see Amazon EC2 On-Demand Pricing.

To determine which instance type best meets your needs, we recommend that you launch an instance and use your own benchmark application. Because you pay by the instance second, it’s convenient and inexpensive to test multiple instance types before making a decision. If your needs change, even after you make a decision, you can change the instance type later. For more information, see Amazon EC2 instance type changes.

Hypervisor type

Amazon EC2 supports the following hypervisors: Xen and Nitro.

Nitro-based instances

• General purpose: M5 | M5a | M5ad | M5d | M5dn | M5n | M5zn | M6a | M6g | M6gd | M6i | M6id | M6idn | M6in | M7a | M7g | M7gd | M7i | M7i-flex | M8g | T3 | T3a | T4g

• Compute optimized: C5 | C5a | C5ad | C5d | C5n | C6a | C6g | C6gd | C6gn | C6i | C6id | C6in | C7a | C7g | C7gd | C7gn | C7i | C7i-flex | C8g

• Memory optimized: R5 | R5a | R5ad | R5b | R5d | R5dn | R5n | R6a | R6g | R6gd | R6i | R6idn | R6in | R6id | R7a | R7g | R7gd | R7i | R7iz | R8g | U-3tb1 | U-6tb1 | U-9tb1 | U-12tb1 | U-18tb1 | U-24tb1 | U7i-12tb | U7in-16tb | U7in-24tb | U7in-32tb | X2gd | X2idn | X2iedn | X2iezn | X8g | z1d

• Storage optimized: D3 | D3en | I3en | I4g | I4i | Im4gn | Is4gen

• Accelerated computing: DL1 | DL2q | G4ad | G4dn | G5 | G5g | G6 | G6e | Gr6 | Inf1 | Inf2 | P3dn | P4d | P4de | P5 | P5e | Trn1 | Trn1n | VT1

• High-performance computing: Hpc6a | Hpc6id | Hpc7a | Hpc7g

• Previous generation: A1

For more information about the supported versions of Nitro hypervisor, see Network feature support in the Amazon EC2 Instance Types Guide.

Xen-based instances

• General purpose: M1 | M2 | M3 | M4 | T1 | T2

• Compute optimized: C1 | C3 | C4

• Memory optimized: R3 | R4 | X1 | X1e

• Storage optimized: D2 | H1 | I2 | I3

• Accelerated computing: F1 | G3 | P2 | P3

AMI virtualization types

The virtualization type of your instance is determined by the AMI that you use to launch it. Current generation instance types support hardware virtual machine (HVM) only. Some previous generation instance types support paravirtual (PV) and some AWS Regions support PV instances. For more information, see Virtualization types.

For best performance, we recommend that you use an HVM AMI. In addition, HVM AMIs are required to take advantage of enhanced networking. HVM virtualization uses hardware-assist technology provided by the AWS platform. With HVM virtualization, the guest VM runs as if it were on a native hardware platform, except that it still uses PV network and storage drivers for improved performance.

Processors

EC2 instances support a variety of processors.

Processors

• Intel processors
• AMD processors
• AWS Graviton processors
• AWS Trainium
• AWS Inferentia

Intel processors

Amazon EC2 instances that run on Intel processors might include the following processor features. Not all instances that run on Intel processors support all of these processor features. For information about which features are available for each instance type, see Amazon EC2 Instance types.

• Intel AES New Instructions (AES-NI) — Intel AES-NI encryption instruction set improves upon the original Advanced Encryption Standard (AES) algorithm to provide faster data protection and greater security. All current generation EC2 instances support this processor feature.

• Intel Advanced Vector Extensions (Intel AVX, Intel AVX2, and Intel AVX-512) — Intel AVX and Intel AVX2 are 256-bit, and Intel AVX-512 is a 512-bit instruction set extension designed for applications that are Floating Point (FP) intensive. Intel AVX instructions improve performance for applications like image and audio/video processing, scientific simulations, financial analytics, and 3D modeling and analysis. These features are only available on instances launched with HVM AMIs.

• Intel Turbo Boost Technology — Intel Turbo Boost Technology processors automatically run cores faster than the base operating frequency.

• Intel Deep Learning Boost (Intel DL Boost) — Accelerates AI deep learning use cases. The 2nd Gen Intel Xeon Scalable processors extend Intel AVX-512 with a new Vector Neural Network Instruction (VNNI/INT8) that significantly increases deep learning inference performance over previous generation Intel Xeon Scalable processors (with FP32) for image recognition/segmentation, object detection, speech recognition, language translation, recommendation systems, reinforcement learning, and more. VNNI may not be compatible with all Linux distributions.

  The following instances support VNNI: M5n, R5n, M5dn, M5zn, R5b, R5dn, D3, D3en, and C6i. C5 and C5d instances support VNNI for only 12xlarge, 24xlarge, and metal instances.

Confusion can result from industry naming conventions for 64-bit CPUs. Chip manufacturer Advanced Micro Devices (AMD) introduced the first commercially successful 64-bit architecture based on the Intel x86 instruction set. Consequently, the architecture is widely referred to as AMD64 regardless of the chip manufacturer. Windows and several Linux distributions follow this practice. This explains why the internal system information on an instance running Ubuntu or Windows displays the CPU architecture as AMD64 even though the instances are running on Intel hardware.

AMD processors

Amazon EC2 instances that run on AMD EPYC processors can help you optimize both cost and performance for your workloads. These instances might support the following processor features. Not all instances that run on AMD processors support all of these processor features. For information about which features are available for each instance type, see Amazon EC2 Instance types.

• AMD Secure Memory Encryption (SME)

• AMD Transparent Single Key Memory Encryption (TSME)

• AMD Advanced Vector Extensions (AVX)

• AMD Secure Encrypted Virtualization-Secure Nested Paging (SEV-SNP)

• Vector Neural Network Instructions (VNNI)

• BFloat16

AWS Graviton processors

AWS Graviton is a family of processors designed to deliver the best price performance for your workloads running on Amazon EC2 instances.

For more information, see Getting started with Graviton.

AWS Trainium

Instances powered by AWS Trainium are purpose built for high-performance, cost-effective deep learning training. You can use these instances to train natural language processing, computer vision, and recommender models used across a broad set of applications, such as speech recognition, recommendation, fraud detection, and image and video classification. Use your existing workflows in popular ML frameworks, such as PyTorch and TensorFlow.

AWS Inferentia

Instances powered by AWS Inferentia are designed to accelerate machine learning. They provide high performance and low latency machine learning inference. These instances are optimized for deploying deep learning (DL) models for applications, such as natural language processing, object detection and classification, content personalization and filtering, and speech recognition.

There are a variety of ways that you can get started:

• Use SageMaker, a fully-managed service that is the easiest way to get started with machine learning models. For more information, see Get Started with SageMaker in the Amazon SageMaker Developer Guide.

• Launch an Inf1 or Inf2 instance using the Deep Learning AMI. For more information, see AWS Inferentia with DLAMI in the AWS Deep Learning AMIs Developer Guide.

• Launch an Inf1 or Inf2 instance using your own AMI and install the AWS Neuron SDK, which enables you to compile, run, and profile deep learning models for AWS Inferentia.

• Launch a container instance using an Inf1 or Inf2 instance and an Amazon ECS-optimized AMI. For more information, see Amazon Linux 2 (Inferentia) AMIs in the Amazon Elastic Container Service Developer Guide.

• Create an Amazon EKS cluster with nodes running Inf1 instances. For more information, see Inferentia support in the Amazon EKS User Guide.