Google Cloud の Compute Engine には、C4A マシンシリーズと A4X マシンシリーズから利用できるさまざまな Arm 搭載サーバーが用意されています。Arm アーキテクチャは電力効率を重視して最適化されているため、優れたコスト パフォーマンスを発揮します。
Arm は、x86 サーバーに比べて電力効率が優れているため、標準サーバーで一般的なプロセッサとなっています。Arm プロセッサ上で動作するデバイスとしては、スマートフォンやノートパソコンなどがあります。Arm CPU は命令セットが少ないため、バッテリーと消費電力を抑えながら、より少ない命令数でより高い処理能力を発揮します。
たとえば、C4A では、Arm Neoverse V2 プロセッサをベースにした Google のカスタム Arm プロセッサである Axion を使用しています。Neoverse V2 は、Armv9 のパフォーマンス、電力、セキュリティが強化された最初の V シリーズ CPU です。ハイ パフォーマンス コンピューティング、機械学習、汎用クラウド コンピューティング向けに設計されています。次のような場合は、C4A 汎用 Arm 仮想マシン(VM)の使用を検討してください。
[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["わかりにくい","hardToUnderstand","thumb-down"],["情報またはサンプルコードが不正確","incorrectInformationOrSampleCode","thumb-down"],["必要な情報 / サンプルがない","missingTheInformationSamplesINeed","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-09-04 UTC。"],[[["\u003cp\u003eGoogle Cloud offers Arm-powered servers in Compute Engine, including the C4A machine series built on Google's custom Axion Arm64-based CPU, which are optimized for power efficiency and deliver better price for performance.\u003c/p\u003e\n"],["\u003cp\u003eThe C4A machine series provides up to 72 vCPUs, 576 GB of DDR5-5600 memory, supports up to 100 Gbps per VM networking performance through Titanium, and is ideal for compute-intensive workloads and Arm-compatible applications.\u003c/p\u003e\n"],["\u003cp\u003eThe Tau T2A machine series, running on the Ampere Altra Arm processor, offers up to 48 physical cores, 4GB of memory per vCPU, and supports only NVMe and gVNIC interfaces, making it suitable for workloads that specifically benefit from the Arm architecture.\u003c/p\u003e\n"],["\u003cp\u003eC4A and Tau T2A machine series both use a single core for each vCPU without simultaneous multithreading (SMT), which provides higher performance per vCPU and is ideal for compute-intensive tasks.\u003c/p\u003e\n"],["\u003cp\u003eArm servers are power efficient and are a great solution for a vast range of workloads, such as ML, image encoding, web and app serving, and more, providing a great alternative to x86 servers.\u003c/p\u003e\n"]]],[],null,["*** ** * ** ***\n\nGoogle Cloud offers a range of Arm powered servers in Compute Engine through\nthe C4A and A4X machine series. Arm architecture is optimized for power efficiency, and as a result can yield better price for performance.\n\nArm processors are common in standard servers due to their power efficiency as\ncompared to x86 servers. Mobile phones and laptops are examples of devices that\nrun on an Arm processor. With an Arm CPU's reduced instruction set, fewer\ninstructions equals greater performance speed with lower battery and power\nconsumption.\n\nFor example, C4A uses Google's custom Arm processor, Axion, which is based on\nthe Arm Neoverse V2 processor. The Neoverse V2 is the first V-series CPU to\nhave Armv9 performance, power, and security enhancements. It is designed for\nhigh performance computing, machine learning, and general-purpose cloud\ncomputing. Consider using C4A general-purpose Arm virtual machines (VMs) for\nany of the following purposes:\n\n- Run compute-intensive workloads that require the ability to scale usage quickly when needed.\n- Optimize for price-performance on Arm-compatible workloads.\n- Build on modern, open source software stacks.\n- Develop and test mobile or embedded systems which use an Arm CPU.\n- Evaluate whether your workload is suitable for an Arm CPU.\n\nTo use GPUs with an Arm-based CPU, choose the A4X machine series, which runs on\nthe NVIDIA GB200 NVL72 platform. VMs created using this machine series have\nattached NVIDIA GB200 Grace Blackwell Superchips. This machine series is\noptimized for massively parallelized Compute Unified Device Architecture (CUDA)\ncompute workloads, such as machine learning (ML) and high performance computing\n(HPC).\n\nA4X machine series\n\n[A4X](/compute/docs/accelerator-optimized-machines#a4x_series) is the first Compute Engine VM with both Arm-based CPUs and attached GPUs. A4X\noffers machine types that have up to 140 vCPUs,\nand 884 GB of memory. A4X uses NVIDIA GB200 GPUs, which offer\n180 GB memory per GPU. A4X has two sockets with NVIDIA Grace Arm CPUs\nconnected to four B200 GPUs with fast chip-to-chip (NVLink C2C) communication.\nA4X is available in the `a4x-highgpu-4g` machine type.\n\nStorage options for A4X instances\n\nA4X can be used with Google Cloud Hyperdisk attached storage and comes with\n12,000 GiB of [Local SSD](/compute/docs/disks/local-ssd). Compute Engine\nautomatically attaches the Local SSD disks to your A4X instances during instance\ncreation.\n\nOS images\n\nA4X instances support public Arm-based [OS images](/compute/docs/images/os-details).\nYou can also [create custom images](/compute/docs/images/create-custom)\nusing a public Arm-based OS image.\n\nC4A machine series\n\n[C4A](/compute/docs/general-purpose-machines#c4a_series) is the first\nArm-based VM built on Google's Axion\nArm64-based CPU. C4A offers machine types with up to 72 vCPUs and 576 GB of\nDDR5-5600 memory. C4A is available in `standard`, `highmem`, and `highcpu`\nmachine types.\n\nC4A is built on [Titanium](/titanium) which uses network offloads and\nenables per VM Tier_1 networking performance of up to 100 Gbps with the\n[gVNIC networking interface](/compute/docs/networking/using-gvnic).\nC4A also supports the NVMe disk interface with Hyperdisk Balanced and Hyperdisk Extreme disks.\n\nSimultaneous multithreading\n\nFor the C4A machine series, each vCPU is backed by a single core with no\n[simultaneous multithreading (SMT)](/compute/docs/instances/set-threads-per-core).\nThus, C4A VMs deliver greater performance per vCPU compared to a VM with SMT\nenabled. While SMT provides benefits to certain workloads, single-threaded cores\nare ideal for compute-intensive workloads because the processes can access the\nentire core instead of sharing it with other processes.\n\nOS images\n\nC4A VMs support public Arm-based [OS images](/compute/docs/images/os-details).\nYou can also [create custom images](/compute/docs/images/create-custom)\nusing a publicly-available Arm-based image.\n\nTau T2A machine series\n\nThe [Tau T2A Arm](/compute/docs/general-purpose-machines#t2a_machines)\nmachine series runs on the 64 core Ampere Altra Arm processor at 3.0 GHz\nall-core frequency. Tau T2A makes it possible to run workloads that run best,\nor exclusively, on Arm.\n\nThe [Tau T2A machine series](/compute/docs/general-purpose-machines#t2a_machines)\nhas predefined machine types of up to 48 physical cores with 4 GB of memory per\nvCPU. Tau T2A machine types run within a single\n[NUMA](https://www.kernel.org/doc/html/v4.18/vm/numa.html)\nnode.\n\nTau T2A machine types support only the NVMe interface for storage, and\n[Google virtual NIC (gVNIC)](/compute/docs/networking/using-gvnic) for\nnetworking. Virtio-Net and SCSI interfaces are not supported. All\npublicly-available Arm [OS images](/compute/docs/images/os-details)\nare configured to use the NVMe and gVNIC interfaces.\ngVNIC is a network interface that is designed specifically for\nCompute Engine. It provides better performance and supports higher\nnetwork bandwidths and throughput.\n\nFor this machine series, each vCPU is backed by a single core with no\nsimultaneous multithreading (SMT).\n\nWorkload recommendations\n\nThe C4A machine series is an excellent choice for a wide range of scale-out and\ncompute-intensive workloads, especially when price performance is a key concern.\nConsider C4A when you are deploying workloads such as the following:\n\n- ML data processing\n- ML inferencing and model serving\n- App serving, web serving, and game serving\n- Embedded systems development\n- Development on CI/CD on Arm\n- Video and image encoding, transcoding, and processing\n- Digital advertising exchanges and serving\n- Cache servers\n- Computational drug discovery\n- Android development\n- Autonomous or conventional automotive software development\n\nWhat's next\n\n- Review the specifications and features of the [A4X machine series](/compute/docs/accelerator-optimized-machines#a4x_series).\n- Review the specifications for the [C4A machine series](/compute/docs/general-purpose-machines#c4a_series).\n- Learn about available [CPU platforms](/compute/docs/cpu-platforms) for Google Cloud.\n- [Create and start a Compute Engine instance](/compute/docs/instances/create-vm-from-public-image) using an Arm OS image."]]