AWS, Cloud Computing

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A Deep Dive into AWS’s Latest M7i-flex Instances


Recently introduced by AWS, the Amazon Elastic Compute Cloud (EC2) M7i-flex instances stand at the forefront of next-generation general-purpose computing. Powered by custom 4th Generation Intel Xeon Scalable processors, known as Sapphire Rapids, these instances promise unmatched performance, a distinction exclusive to the AWS platform. Featuring an impressive 4:1 ratio of memory to virtual CPU (vCPU), the M7i-flex instances emerge as a formidable solution tailored to excel across a diverse spectrum of workloads. In this blog post, we explore the vital features, advantages, and specifications of the M7i-flex instances.


Positioned as an excellent initial option, these instances are well-suited for applications that may not fully utilize all available compute resources. M7i-flex instances demonstrate efficient resource utilization, delivering a baseline performance level while allowing scalability to the full compute performance most of the time.

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Amazon EC2 M7i-Flex instances

Amazon EC2 M7i-Flex instances emerge as a formidable solution, excelling across diverse workloads, with an impressive 4:1 ratio of memory to virtual CPU (vCPU). Setting a groundbreaking standard in cloud computing, these instances outperform comparable Intel processors in rival cloud services, showcasing up to a 15% enhancement in performance.

The superior capability results in a substantial 19% improvement in price performance compared to their predecessors, the M6i instances. Available in sizes ranging from large to 8xlarge, M7i-flex instances provide versatile configurations with up to 32 vCPUs and 128 GiB of memory.

The availability of M7i-flex instances spans key AWS regions, including the US East (Ohio, N. Virginia), US West (Oregon), and Europe (Ireland), ensuring widespread accessibility for users.


  • Empowered by the 4th Generation Intel Xeon Scalable processors: The driving force behind M7i-flex instances lies in their utilization of exclusive custom 4th Generation Intel Xeon Scalable processors, featuring an all-core turbo frequency of 3.2 GHz (with a maximum core turbo frequency of 3.8 GHz). These distinct processors are solely accessible through AWS and stand out for delivering superior performance compared to equivalent Intel processors. Additionally, M7i-flex instances support continuous memory encryption using Intel Total Memory Encryption (TME).
  • High-throughput interfaces: M7i-flex instances utilize DDR5 memory, offering enhanced bandwidth in comparison to M6i instances. These instances support up to 10 Gbps bandwidth to Amazon Elastic Block Store (Amazon EBS) and a networking bandwidth of up to 12.5 Gbps.
  • New accelerators: The 4th Generation Intel Xeon Scalable processors incorporate four new built-in accelerators, with Advance Matrix Extensions (AMX) available on M7i-flex and M7i instances. AMX accelerates matrix multiplication operations, which is particularly beneficial for applications like CPU-based machine learning.
  • Developed on the Nitro System: The AWS Nitro System offers versatile configurations, enabling AWS to flexibly design and swiftly introduce a diverse range of Amazon EC2 instance types. These instances have an expanding array of compute, storage, memory, and networking options. Nitro Cards play a key role by offloading and accelerating I/O functions, thereby enhancing the overall performance of the system.


  • Enhanced cost efficiency: M7i-flex instances provide a straightforward approach to cost optimization for most general-purpose workloads, presenting up to a 19% improvement in price performance compared to M6i instances. Additionally, these instances offer larger size options, facilitating consolidation and the execution of more demanding and extensive workloads.
  • Versatility and options: M7i-flex and M7i instances contribute to the extensive and comprehensive range of Amazon EC2 instances available on the AWS platform. M7i-flex provides the five most frequently used sizes, spanning from large to 8xlarge.
  • Enhanced Resource Efficiency: M7i-flex instances are constructed using the AWS Nitro System, which blends dedicated hardware with a lightweight hypervisor. Nitro efficiently allocates nearly all the compute and memory resources from the host hardware to your instances, enhancing overall performance and security. Amazon EC2 instances built on the Nitro System demonstrate a throughput performance over 15% higher on workloads compared to counterparts in other cloud providers utilizing the same CPU.

Below are the specifications for the M7i-Flex instances



Amazon EC2 Flex instances provide a streamlined solution for customers who may not fully leverage the compute resources of their Amazon EC2 instances, offering enhanced price performance for general-purpose workloads. M7i-flex instances effectively utilize compute resources and can scale up to the full compute performance, showcasing their purpose-built design to optimize cost and performance.

Drop a query if you have any questions regarding M7i-flex instances and we will get back to you quickly.

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1. What purchasing options are available for M7i-Flex instances?

ANS: – M7i-Flex instances can be acquired through various purchasing options, including On-Demand, Reserved Instances, Savings Plans, and Spot instances.

2. How do M7i-flex instances enhance network performance compared to M6i instances?

ANS: – M7i-flex instances utilize DDR5 memory, providing enhanced bandwidth. They offer support for up to 10 Gbps bandwidth to Amazon Elastic Block Store (Amazon EBS) and a networking bandwidth of up to 12.5 Gbps, showcasing improved network throughput compared to M6i instances.

3. Can M7i-flex instances be used for CPU-based machine learning applications?

ANS: – M7i-flex instances incorporate Advance Matrix Extensions (AMX) on the 4th Generation Intel Xeon Scalable processors, which accelerate matrix multiplication operations, making them beneficial for CPU-based machine learning applications.

WRITTEN BY Abhilasha D

Abhilasha D is a Research Associate-DevOps at CloudThat. She is focused on gaining knowledge of Cloud environment and DevOps tools. She has keen interest in learning and researching on emerging technologies.



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