Compute optimized instances - Amazon Elastic Compute Cloud
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Compute optimized instances

Compute optimized instances are ideal for compute-bound applications that benefit from high-performance processors.

C5 and C5n instances

These instances are well suited for the following:

  • Batch processing workloads

  • Media transcoding

  • High-performance web servers

  • High-performance computing (HPC)

  • Scientific modeling

  • Dedicated gaming servers and ad serving engines

  • Machine learning inference and other compute-intensive applications

Bare metal instances, such as c5.metal, provide your applications with direct access to physical resources of the host server, such as processors and memory.

C6i and C6id instances

These instances are ideal for running advanced, compute-intensive workloads, such as the following:

  • High-performance computing (HPC)

  • Batch processing

  • Ad serving

  • Video encoding

  • Distributed analytics

  • Highly scalable multiplayer gaming

C6in instances

These instances are well suited for compute-intensive workloads such as the following:

  • Distributed computing applications

  • Network virtual appliances

  • Data analytics

  • High Performance Computing (HPC)

  • CPU-based AI/ML

For more information, see Amazon EC2 C6i Instances.

Hardware specifications

The following is a summary of the hardware specifications for compute optimized instances. A virtual central processing unit (vCPU) represents a portion of the physical CPU assigned to a virtual machine (VM). For x86 instances, there are two vCPUs per core. For Graviton instances, there is one vCPU per core.

Instance type Default vCPUs Memory (GiB)
c1.medium 2 1.70
c1.xlarge 8 7.00
c3.large 2 3.75
c3.xlarge 4 7.50
c3.2xlarge 8 15.00
c3.4xlarge 16 30.00
c3.8xlarge 32 60.00
c4.large 2 3.75
c4.xlarge 4 7.50
c4.2xlarge 8 15.00
c4.4xlarge 16 30.00
c4.8xlarge 36 60.00
c5.large 2 4.00
c5.xlarge 4 8.00
c5.2xlarge 8 16.00
c5.4xlarge 16 32.00
c5.9xlarge 36 72.00
c5.12xlarge 48 96.00
c5.18xlarge 72 144.00
c5.24xlarge 96 192.00
c5.metal 96 192.00
c5a.large 2 4.00
c5a.xlarge 4 8.00
c5a.2xlarge 8 16.00
c5a.4xlarge 16 32.00
c5a.8xlarge 32 64.00
c5a.12xlarge 48 96.00
c5a.16xlarge 64 128.00
c5a.24xlarge 96 192.00
c5ad.large 2 4.00
c5ad.xlarge 4 8.00
c5ad.2xlarge 8 16.00
c5ad.4xlarge 16 32.00
c5ad.8xlarge 32 64.00
c5ad.12xlarge 48 96.00
c5ad.16xlarge 64 128.00
c5ad.24xlarge 96 192.00
c5d.large 2 4.00
c5d.xlarge 4 8.00
c5d.2xlarge 8 16.00
c5d.4xlarge 16 32.00
c5d.9xlarge 36 72.00
c5d.12xlarge 48 96.00
c5d.18xlarge 72 144.00
c5d.24xlarge 96 192.00
c5d.metal 96 192.00
c5n.large 2 5.25
c5n.xlarge 4 10.50
c5n.2xlarge 8 21.00
c5n.4xlarge 16 42.00
c5n.9xlarge 36 96.00
c5n.18xlarge 72 192.00
c5n.metal 72 192.00
c6a.large 2 4.00
c6a.xlarge 4 8.00
c6a.2xlarge 8 16.00
c6a.4xlarge 16 32.00
c6a.8xlarge 32 64.00
c6a.12xlarge 48 96.00
c6a.16xlarge 64 128.00
c6a.24xlarge 96 192.00
c6a.32xlarge 128 256.00
c6a.48xlarge 192 384.00
c6a.metal 192 384.00
c6i.large 2 4.00
c6i.xlarge 4 8.00
c6i.2xlarge 8 16.00
c6i.4xlarge 16 32.00
c6i.8xlarge 32 64.00
c6i.12xlarge 48 96.00
c6i.16xlarge 64 128.00
c6i.24xlarge 96 192.00
c6i.32xlarge 128 256.00
c6i.metal 128 256.00
c6id.large 2 4.00
c6id.xlarge 4 8.00
c6id.2xlarge 8 16.00
c6id.4xlarge 16 32.00
c6id.8xlarge 32 64.00
c6id.12xlarge 48 96.00
c6id.16xlarge 64 128.00
c6id.24xlarge 96 192.00
c6id.32xlarge 128 256.00
c6id.metal 128 256.00
c6in.large 2 4.00
c6in.xlarge 4 8.00
c6in.2xlarge 8 16.00
c6in.4xlarge 16 32.00
c6in.8xlarge 32 64.00
c6in.12xlarge 48 96.00
c6in.16xlarge 64 128.00
c6in.24xlarge 96 192.00
c6in.32xlarge 128 256.00
cc2.8xlarge 32 60.50

The compute optimized instances use the following processors.

AMD processors
  • 2nd generation AMD EPYC processors (AMD EPYC 7R32): C5a, C5ad

  • 3rd generation AMD EPYC processors (AMD EPYC 7R13): C6a

Intel processors
  • Intel Xeon Scalable processors (Haswell E5-2666 v3): C4

  • Intel Xeon Scalable processors (Skylake 8124): C5n

  • Intel Xeon Scalable processors (Skylake 8124M or Cascade Lake 8223CL): Smaller C5 and C5d

  • 2nd generation Intel Xeon Scalable processors (Cascade Lake 8275CL): Larger C5 and C5d

  • 3rd generation Intel Xeon Scalable processors (Ice Lake 8375C): C6i, C6id

For more information, see Amazon EC2 Instance Types.

Instance performance

EBS-optimized instances enable you to get consistently high performance for your EBS volumes by eliminating contention between Amazon EBS I/O and other network traffic from your instance. Some compute optimized instances are EBS-optimized by default at no additional cost. For more information, see Amazon EBS–optimized instances.

Network performance

You can enable enhanced networking on supported instance types to provide lower latencies, lower network jitter, and higher packet-per-second (PPS) performance. Most applications do not consistently need a high level of network performance, but can benefit from access to increased bandwidth when they send or receive data. For more information, see Enhanced networking on Windows.

The following is a summary of network performance for compute optimized instances that support enhanced networking.

Instance type Baseline bandwidth (Gbps) Burst bandwidth (Gbps) Enhanced networking features
c1.medium 0.3 1.2 Not supported
c1.xlarge 1.0 10.0 Not supported
c3.large 0.5 1.2 Not supported
c3.xlarge 0.7 10.0 Not supported
c3.2xlarge 1.0 10.0 Not supported
c3.4xlarge 2.0 10.0 Not supported
c3.8xlarge 5.0 10.0 Not supported
c4.large 0.625 1.2 Not supported
c4.xlarge 1.25 2.8 Not supported
c4.2xlarge 2.5 10.0 Not supported
c4.4xlarge 5.0 10.0 Not supported
c4.8xlarge 5.0 10.0 Not supported
c5.large 0.75 10.0 ENA
c5.xlarge 1.25 10.0 ENA
c5.2xlarge 2.5 10.0 ENA
c5.4xlarge 5.0 10.0 ENA
c5.9xlarge 12.0 - ENA
c5.12xlarge 12.0 - ENA
c5.18xlarge 25.0 - ENA
c5.24xlarge 25.0 - ENA
c5.metal 25.0 - ENA
c5a.large 0.75 10.0 ENA
c5a.xlarge 1.25 10.0 ENA
c5a.2xlarge 2.5 10.0 ENA
c5a.4xlarge 5.0 10.0 ENA
c5a.8xlarge 10.0 - ENA
c5a.12xlarge 12.0 - ENA
c5a.16xlarge 20.0 - ENA
c5a.24xlarge 20.0 - ENA
c5ad.large 0.75 10.0 ENA
c5ad.xlarge 1.25 10.0 ENA
c5ad.2xlarge 2.5 10.0 ENA
c5ad.4xlarge 5.0 10.0 ENA
c5ad.8xlarge 10.0 - ENA
c5ad.12xlarge 12.0 - ENA
c5ad.16xlarge 20.0 - ENA
c5ad.24xlarge 20.0 - ENA
c5d.large 0.75 10.0 ENA
c5d.xlarge 1.25 10.0 ENA
c5d.2xlarge 2.5 10.0 ENA
c5d.4xlarge 5.0 10.0 ENA
c5d.9xlarge 12.0 - ENA
c5d.12xlarge 12.0 - ENA
c5d.18xlarge 25.0 - ENA
c5d.24xlarge 25.0 - ENA
c5d.metal 25.0 - ENA
c5n.large 3.0 25.0 ENA
c5n.xlarge 5.0 25.0 ENA
c5n.2xlarge 10.0 25.0 ENA
c5n.4xlarge 15.0 25.0 ENA
c5n.9xlarge 50.0 - ENA | EFA
c5n.18xlarge 100.0 - ENA | EFA
c5n.metal 100.0 - ENA | EFA
c6a.large 0.781 12.5 ENA
c6a.xlarge 1.562 12.5 ENA
c6a.2xlarge 3.125 12.5 ENA
c6a.4xlarge 6.25 12.5 ENA
c6a.8xlarge 12.5 - ENA
c6a.12xlarge 18.75 - ENA
c6a.16xlarge 25.0 - ENA
c6a.24xlarge 37.5 - ENA
c6a.32xlarge 50.0 - ENA
c6a.48xlarge 50.0 - ENA | EFA
c6a.metal 50.0 - ENA | EFA
c6i.large 0.781 12.5 ENA
c6i.xlarge 1.562 12.5 ENA
c6i.2xlarge 3.125 12.5 ENA
c6i.4xlarge 6.25 12.5 ENA
c6i.8xlarge 12.5 - ENA
c6i.12xlarge 18.75 - ENA
c6i.16xlarge 25.0 - ENA
c6i.24xlarge 37.5 - ENA
c6i.32xlarge 50.0 - ENA | EFA
c6i.metal 50.0 - ENA | EFA
c6id.large 0.781 12.5 ENA
c6id.xlarge 1.562 12.5 ENA
c6id.2xlarge 3.125 12.5 ENA
c6id.4xlarge 6.25 12.5 ENA
c6id.8xlarge 12.5 - ENA
c6id.12xlarge 18.75 - ENA
c6id.16xlarge 25.0 - ENA
c6id.24xlarge 37.5 - ENA
c6id.32xlarge 50.0 - ENA | EFA
c6id.metal 50.0 - ENA | EFA
c6in.large 3.125 25.0 ENA
c6in.xlarge 6.25 30.0 ENA
c6in.2xlarge 12.5 40.0 ENA
c6in.4xlarge 25.0 50.0 ENA
c6in.8xlarge 50.0 - ENA
c6in.12xlarge 75.0 - ENA
c6in.16xlarge 100.0 - ENA
c6in.24xlarge 150.0 - ENA
c6in.32xlarge 400.0 - ENA | EFA

† These instances have a baseline bandwidth and can use a network I/O credit mechanism to burst beyond their baseline bandwidth on a best effort basis. For more information, see instance network bandwidth.

Amazon EBS I/O performance

Amazon EBS optimized instances use an optimized configuration stack and provide additional, dedicated capacity for Amazon EBS I/O. This optimization provides the best performance for your Amazon EBS volumes by minimizing contention between Amazon EBS I/O and other traffic from your instance.

For more information, see Amazon EBS–optimized instances.

Instance store volume I/O performance

If you use all the SSD-based instance store volumes available to your instance, you can get up to the IOPS (4,096 byte block size) performance listed in the following table (at queue depth saturation). Otherwise, you get lower IOPS performance.

Instance Size 100% Random Read IOPS Write IOPS
c1.medium 33600 8000
c1.xlarge 144000 32000
c3.large 18240 16000
c3.xlarge 38400 25600
c3.2xlarge 64000 44800
c3.4xlarge 118400 76800
c3.8xlarge 227200 140800
c5ad.large 16283 7105
c5ad.xlarge 32566 14211
c5ad.2xlarge 65132 28421
c5ad.4xlarge 130262 56842
c5ad.8xlarge 260526 113684
c5ad.12xlarge 412500 180000
c5ad.16xlarge 521052 227368
c5ad.24xlarge 825000 360000
c5d.large 20000 9000
c5d.xlarge 40000 18000
c5d.2xlarge 80000 37000
c5d.4xlarge 175000 75000
c5d.9xlarge 350000 170000
c5d.12xlarge 700000 340000
c5d.18xlarge 700000 340000
c5d.24xlarge 1400000 680000
c5d.metal 1400000 680000
c6id.large 33542 16771
c6id.xlarge 67083 33542
c6id.2xlarge 134167 67084
c6id.4xlarge 268333 134167
c6id.8xlarge 536666 268334
c6id.12xlarge 804998 402500
c6id.16xlarge 1073332 536668
c6id.24xlarge 1609996 805000
c6id.32xlarge 2146664 1073336
c6id.metal 2146664 1073336

As you fill the SSD-based instance store volumes for your instance, the number of write IOPS that you can achieve decreases. This is due to the extra work the SSD controller must do to find available space, rewrite existing data, and erase unused space so that it can be rewritten. This process of garbage collection results in internal write amplification to the SSD, expressed as the ratio of SSD write operations to user write operations. This decrease in performance is even larger if the write operations are not in multiples of 4,096 bytes or not aligned to a 4,096-byte boundary. If you write a smaller amount of bytes or bytes that are not aligned, the SSD controller must read the surrounding data and store the result in a new location. This pattern results in significantly increased write amplification, increased latency, and dramatically reduced I/O performance.

SSD controllers can use several strategies to reduce the impact of write amplification. One such strategy is to reserve space in the SSD instance storage so that the controller can more efficiently manage the space available for write operations. This is called over-provisioning. The SSD-based instance store volumes provided to an instance don't have any space reserved for over-provisioning. To reduce write amplification, we recommend that you leave 10% of the volume unpartitioned so that the SSD controller can use it for over-provisioning. This decreases the storage that you can use, but increases performance even if the disk is close to full capacity.

For instance store volumes that support TRIM, you can use the TRIM command to notify the SSD controller whenever you no longer need data that you've written. This provides the controller with more free space, which can reduce write amplification and increase performance. For more information, see Instance store volume TRIM support.

Release notes

  • C4 instances and instances built on the Nitro System require 64-bit EBS-backed HVM AMIs. They have high-memory and require a 64-bit operating system to take advantage of that capacity. HVM AMIs provide superior performance in comparison to paravirtual (PV) AMIs on high-memory instance types. In addition, you must use an HVM AMI to take advantage of enhanced networking.

  • Instances built on the Nitro System have the following requirements:

    The current Amazon Windows AMIs meet these requirements.

  • To get the best performance from your C6i instances, ensure that they have ENA driver version 2.2.3 or later. Using an ENA driver earlier than version 2.0.0 with these instances causes network interface attachment failures. The following AMIs have a compatible ENA driver.

    • Amazon Windows AMI from May 2021 or later

  • Instances built on the Nitro System instances support a maximum of 28 attachments, including network interfaces, EBS volumes, and NVMe instance store volumes. For more information, see Nitro System volume limits.

  • Launching a bare metal instance boots the underlying server, which includes verifying all hardware and firmware components. This means that it can take 20 minutes from the time the instance enters the running state until it becomes available over the network.

  • To attach or detach EBS volumes or secondary network interfaces from a bare metal instance requires PCIe native hotplug support.

  • Bare metal instances use a PCI-based serial device rather than an I/O port-based serial device. The upstream Linux kernel and the latest Amazon Linux AMIs support this device. Bare metal instances also provide an ACPI SPCR table to enable the system to automatically use the PCI-based serial device. The latest Windows AMIs automatically use the PCI-based serial device.

  • There is a limit on the total number of instances that you can launch in a Region, and there are additional limits on some instance types. For more information, see How many instances can I run in Amazon EC2? in the Amazon EC2 FAQ.