Google Cloud Launched M4N Virtual Machine Series

The new cloud instances aim to lower software licensing costs for memory-intensive enterprise database workloads.

Updated on Sept. 18, 2026 in Data Centers

Isometric editorial illustration of a row of server cabinets with metallic orange vents and connecting network cables in a clean data hall. — Google Cloud introduced the M4N virtual machine series on Tuesday, allowing enterprises to scale memory capacity for large database workloads independently from compute power. AI Illustration. Upload story photo >

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Google Cloud has released its M4N virtual machine instance series, designed to optimize compute resource allocation for massive databases. The new series supports applications such as SAP HANA and SQL Server by decoupling memory capacity from core counts.

Why it matters

Traditional core-based licensing models often force companies to over-provision compute power just to gain sufficient memory. By allowing more granular resource matching, this architecture helps enterprises avoid paying for unneeded vCPUs.

The M4N instances feature 5th Gen Intel Xeon Scalable processors and support up to 5,952GB of DDR5 RAM. These instances provide 26GB of memory per vCPU and utilize the Titanium offload architecture to deliver 400 Gbps network throughput.

The players

Google Cloud

This division of Alphabet Inc. provides cloud computing services and infrastructure to enterprises globally.

The details

The M4N series scales between 16 and 224 vCPUs while offering aggregate storage performance of 25 GiB/s through Hyperdisk Extreme. This design specifically targets electronic health record systems and Oracle database deployments that require high throughput and massive memory availability.

Google Cloud officially launched the M4N virtual machine instance series on September 18, 2026.

The Tech Race

The M4N series represents a shift toward disaggregated infrastructure, moving away from rigid hardware bundles that have long dictated enterprise software costs. This positions Google Cloud to capture market share from competitors by directly addressing the financial inefficiencies of current database licensing models.

Enterprise IT managers and database administrators can expect more flexibility in configuring cloud environments to meet specific application requirements. By reducing the need to over-provision compute resources, companies may see a measurable decrease in monthly cloud expenditure for their database workloads.

The takeaway

Enterprises should audit their current core-to-memory ratios to determine if switching to disaggregated instance types like the M4N series aligns with their licensing agreements. Optimizing hardware selection remains a primary lever for reducing cloud operating expenses in high-performance computing environments.