# Ubuntu and Arm: running agentic AI workloads with kernel 7.0 and 15 years of support

- **Published on:** 2026-05-26
- **Category:** News
- **Original page:** https://linuxgratis.com/en/articles/ejecutar-cargas-agenticas-ia-arm-ubuntu

Canonical explains how to run agentic AI workloads on Arm and Ubuntu 26.04 LTS: CPUs with up to 136 Neoverse V3 cores, Arm64 kernel livepatching and 15 years of support with Ubuntu Pro.

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Canonical has published a technical guide on running agentic AI workloads using Arm processors alongside [Ubuntu](/en/ubuntu). The reasoning is straightforward: AI agents chain together model calls, tools and APIs, which means sustained, power-efficient compute. That profile maps well onto recent Arm silicon.

## The hardware in question

The article uses as its reference an Arm CPU with up to **136 Neoverse V3 cores** laid out in a **dual-chiplet** design built on TSMC's **3nm** process. The figures Canonical gives are specific: a **300W** TDP for maximum throughput, memory latency **below 100ns**, **12 DDR5 channels** and **6GB/s of bandwidth per core**. At the rack level, they cite **272 dedicated cores** per 1OU dual-node server unit, which says a lot about the density they are targeting for data centres.

These aren't hand-wavy claims. They are the numbers that explain why Arm keeps coming up in AI conversations, where power draw and density per rack matter as much as raw performance.

## What Ubuntu brings to the table

The software side is where Ubuntu earns its place. **Ubuntu 26.04 LTS** ships with the **Linux 7.0** kernel and enterprise support of up to **15 years** through Ubuntu Pro. For anyone running fleets of Arm servers, two details stand out:

- **Kernel livepatching on Arm64**: applying kernel security patches without rebooting. This existed on other architectures already, and it now covers Arm64 servers too, which matters when you have agents running continuously and can't afford downtime windows.
- **Arm64 features at the system level**: support for **MPAM** (control over shared resources such as cache and memory bandwidth) and **nested virtualization**.

The post also points to **Rust** entering system components, with `sudo-rs` and `coreutils` rewritten in the language for memory safety, plus alignment with **MTE (Memory Tagging Extension)**, present in Neoverse V3. This is the direction Ubuntu has been moving in for a while: cutting whole classes of memory bugs out from the base of the system.

## The rest of the stack

Canonical takes the chance to remind readers that its infrastructure tooling has native Arm64 support: **MAAS** for bare-metal provisioning, **OpenStack**, **MicroCloud**, **Ceph** for storage, **LXD** for containers and virtual machines, and **Canonical Kubernetes**. The message is that you can build the full stack, from metal to orchestrator, on Arm without stepping outside official support.

Cindy Goldberg, VP of Cloud and Silicon Partnerships at Canonical, frames the announcement within a long-running collaboration with Arm. Eddie Ramirez, VP of Go-to-Market at Arm, sums up the motivation: agentic AI calls for a new class of infrastructure where performance, efficiency and scalability are engineered together.

## Why it matters to you

If you run AI agents in production, or you are weighing up where to host them, the practical takeaway is clear: Arm is no longer a niche option for this kind of workload. Pairing many efficient cores with Ubuntu's long support and hot kernel patching cuts two costs that hurt in operations: the electricity bill and maintenance downtime.

Canonical also notes that Ubuntu was the first enterprise distribution to support Arm servers, back with Ubuntu 12.04 LTS in 2012. Fourteen years on, that track record shows in how polished the architecture support has become.

## Source

Based on the article by Youssef Eltoukhy published by Canonical on 26 May 2026: [Run agentic workloads on Arm and Ubuntu](https://ubuntu.com/blog/run-agentic-workloads-on-arm-and-ubuntu).