Decision makers and builders today face a constant challenge: managing rising cloud costs while delivering the performance their customers demand. As applications evolve to use scale-out microservices and handle ever-growing data volumes, organizations need maximum efficiency from their underlying infrastructure to support their growing general-purpose workloads.
To meet this need, we’re excited to announce our latest Axion-based virtual machine series: N4A, available in preview on Compute Engine, Google Kubernetes Engine (GKE), Dataproc, and Batch, with support in Dataflow and other services coming soon.
N4A is the most cost-effective N-series VM to date, delivering **up to 2x better price-performance and 80% better performance-per-watt **than comparable current-generation x86-base…
Decision makers and builders today face a constant challenge: managing rising cloud costs while delivering the performance their customers demand. As applications evolve to use scale-out microservices and handle ever-growing data volumes, organizations need maximum efficiency from their underlying infrastructure to support their growing general-purpose workloads.
To meet this need, we’re excited to announce our latest Axion-based virtual machine series: N4A, available in preview on Compute Engine, Google Kubernetes Engine (GKE), Dataproc, and Batch, with support in Dataflow and other services coming soon.
N4A is the most cost-effective N-series VM to date, delivering **up to 2x better price-performance and 80% better performance-per-watt **than comparable current-generation x86-based VMs. This makes it easier for customers to further optimize the Total Cost of Ownership (TCO) for a broad range of general-purpose workloads. We see this with cloud-native businesses running scale-out web servers and microservices on GKE, enterprise teams managing backend application servers and mid-sized databases, and engineering organizations operating large CI/CD build farms.
At Google Cloud, we co-design our compute offerings with storage, networking and software at every layer of the stack, from orchestrators to runtimes, to deliver exceptional system-level performance and cost-efficiency. N4A’s breakthrough price-performance is powered by our latest-generation Google Axion Processors, built on the Arm® Neoverse® N3 compute core, Google Dynamic Resource Management (DRM) technology, and Titanium, Google Cloud’s custom-designed hardware and software system that offloads networking and storage processing to free up the CPU. Titanium is part of Google Cloud’s vertically integrated software stack — from the custom silicon in our servers to our planet-scale network traversing 7.75 million kilometers of terrestrial and subsea fiber across 42 regions — that is engineered to maximize efficiency and provide the ultra-low latency and high bandwidth to customers at global scale.
Redefining general-purpose compute and enabling AI inference
N4A is engineered for versatility, with a feature set to support your general-purpose and CPU-based AI workloads. It comes in predefined and custom shapes, with up to 64 vCPUs and 512GB of DDR5 in high-cpu (2GB of memory per vCPU), standard (4GB per vCPU), and high-memory (8GB per vCPU) configurations, with instance networking up to 50 Gbps of bandwidth. N4A VMs feature support for our latest generation Hyperdisk storage options, including Hyperdisk Balanced, Hyperdisk Throughput, and Hyperdisk ML (coming later), providing up to 160K IOPS, 2.4GB/s of throughput per instance.
N4A performs well across a range of industry-standard benchmarks that represent the key workloads our customers run every day. For example, relative to comparable current-generation x86-based VM offerings, N4A delivers up to 105% better price-performance for compute-bound workloads, up to 90% better price-performance for scale-out web servers, up to 85% better price-performance for Java applications, and up to** 20%** better price-performance for general-purpose databases.
Footnote: As of October 2025. Performance based on the estimated SPECrate®2017_int_base, estimated SPECjbb2015, MySQL Transactions/minute (RO), and Google internal Nginx Reverse Proxy benchmark scores run in production on comparable latest-generation generally-available VMs with general purpose storage types. Price-performance claims based on published and upcoming list prices for Google Cloud.
In the real world, early adopters are seeing dramatic price-performance improvements from the new N4A instances.
“At ZoomInfo, we operate a massive data intelligence platform where efficiency is paramount. Our core data processing pipelines, which are critical for delivering timely insights to our customers, run extensively on Dataflow and Java services in GKE. In our preview of the new N4A instances, we measured a 60% improvement in price-performance for these key workloads compared to their x86-based counterparts. This allows us to scale our platform more efficiently and deliver more value to our customers, faster.” - Sergei Koren, Chief Infrastructure Architect, ZoomInfo
“Organizations today need performance, efficiency, flexibility, and scale to meet the computing demands of the AI era; this requires the close collaboration and co-design that is at the heart of our partnership with Google Cloud. As N4A redefines cost-efficiency, customers gain a new level of infrastructure optimization, enabling enterprises to choose the right infrastructure for their workload requirements with Arm and Google Cloud.” - Bhumik Patel, Director, Server Ecosystem Development, Infrastructure Business, Arm
Granular control with Custom Machine Types and Hyperdisk
A key advantage of our N-series VMs has always been flexibility, and with N4A, we are bringing one of our most popular features to the Axion family for the first time: Custom Machine Types (CMT). Instead of fitting your workload into a predefined shape, CMTs on N4A lets you independently configure the amount of vCPU and memory to meet your application’s unique needs. This ability to right-size your instances means you pay only for the resources you use, minimizing waste and optimizing your total cost of ownership.
This same principle of matching resources to your specific workload applies to storage. N4A VMs feature support for our latest generation of Hyperdisk, allowing you to select the perfect storage profile for your application’s needs:
Hyperdisk Balanced: Offers an optimal mix of performance and cost for the majority of general-purpose workloads, with up to 160K IOPs per N4A VM.
Hyperdisk Throughput: Delivers up to 2.4GiBps of max throughput for bandwidth-intensive analytics workloads like Hadoop or Kafka, providing high-capacity storage at an excellent value.
Hyperdisk ML (post GA): Purpose-built for AI/ML workloads, allows you to attach a single disk containing your model weights or datasets to up to 32 N4A instances simultaneously for large-scale inference or training tasks.
Hyperdisk Storage Pools: Instead of provisioning capacity and performance on a per-volume basis, allows you to provision performance and capacity in aggregate, further optimizing costs by up to 50% and simplifying management.
“At Vimeo, we have long relied on Custom Machine Types to efficiently manage our massive video transcoding platform. Our initial tests on the new Axion-based N4A instances have been very compelling, unlocking a new level of efficiency. We’ve observed a 30% improvement in performance for our core transcoding workload compared to comparable x86 VMs. This points to a clear path for improving our unit economics and scaling our services more profitably, without changing our operational model.” - Joe Peled, Sr. Director of Hosting & Delivery Ops
A growing Arm-based Axion portfolio for customer choice
C-series VMs are designed for workloads that require consistently high performance, e.g., medium-to-large-scale databases and in-memory caches. Alongside them, N-series VMs have been a key Compute Engine pillar, offering a balance of price-performance and flexibility, lowering the cost of running workloads with variable resource needs such as scale-out Java/GKE workloads. We released our first Axion-based machine series, C4A, in October 2024, and the introduction of N4A complements C4A, providing a range of Google Axion instances suited to your workloads’ precise needs.
On top of that, GKE unlocks significant price-performance advantages by orchestrating Axion-based C4A and N4A machine types. GKE leverages Custom Compute Classes to provision and mix these machine types, matching workloads to the right hardware. This automated, heterogeneous cluster management allows teams to optimize their total cost of ownership across their entire application stack.
Also joining the Axion family is C4A.metal, Google Cloud’s first Axion bare metal instance that helps builders meet use cases that require access to the underlying physical server to run specialized applications in a non-virtualized environment, such as automotive systems development, workloads with strict licensing requirements, and Android software development. C4A.metal will be available in preview soon.
Supported by the broad and mature Arm ecosystem, adopting Axion is easier than ever, and the combination of C4A and N4A can help you lower the total cost of running your business, without compromising on performance or workload-specific requirements:
N4A for cost optimization and flexibility. Deliberately engineered for general-purpose workloads that need a balance of price and performance, including scale-out web servers, microservices, containerized applications, open-source databases, batch, data analytics, development environments, data preparation and AI/ML experimentation.
C4A for consistently high performance, predictability, and control. Powering workloads where every microsecond counts, such as medium- to large-scale databases, in-memory caches, cost-effective AI/ML inference, and high-traffic gaming servers. C4A delivers consistent performance, offering a controlled maintenance experience for mission-critical workloads, networking bandwidth up to 100 Gbps, and next-generation Titanium Local SSD storage.
“Migrating to Google Cloud’s Axion portfolio gave us a critical competitive advantage. We slashed our compute consumption by 20% while maintaining low and stable latency with C4A instances, such as our Supply-Side Platform (SSP) backend service. Additionally, C4A enabled us to leverage Hyperdisk with precisely the IOPS we need for our stateful workloads, regardless of instance size. This flexibility gives us the best of both worlds - allowing us to win more ad auctions for our clients while significantly improving our margins. We’re now testing the N4A family by running some of our key workloads that require the most flexibility, such as our API relay service. We are happy to share that several applications running in production are consuming 15% less CPU compared to our previous infrastructure, reducing our costs further, while ensuring that the right instance backs the workload characteristics required.” - Or Ben Dahan, Cloud & Software Architect at Rise
Get started with N4A today
N4A is available during preview in the following Google Cloud regions: us-central1 (Iowa), us-east4 (N. Virginia), **europe-west3 (Frankfurt) **and europe-west4 (Netherlands) with more regions to follow.
We can’t wait to see what you build. To get access, sign-up here. To learn more, check out the N4A documentation.
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