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Tracing a memory leak bug in PID 1 and contributing an upstream fix: a Linux support story | Canonical MAAS installation: bare metal provisioning is easier than ever | Canonical Januscape vulnerability CVE-2026-53359 mitigations available | Canonical Managing Ubuntu on bare metal at scale | Canonical Ubuntu Server: a platform made for enterprise scale | Canonical Building an open source chain of trust: new research uncovers key blockers and ways forward | Canonical Beyond safety and security: Why automotive open source demands dependability  | Canonical DirtyClone Linux kernel local privilege escalation vulnerability fixes available | Canonical pedit COW kernel local privilege escalation vulnerability mitigations | Canonical Canonical becomes Gold Sponsor of Trifecta Tech Foundation | Canonical Challenges designers face in open source (and how to fix them) | Canonical Hunting a 16-year-old SQLite bug with TLA+: is dqlite affected? | Canonical Anbox Cloud on C4A metal: Android, at scale, without friction | Canonical Canonical announces live kernel patching for Arm64 | Canonical How to use RISC-V custom instructions with Ubuntu | Canonical Ubuntu Summit 26.04: connected by open source | Canonical So you need to add microcontrollers to your fleet: now what? | Canonical Validating real-world skills through Canonical Academy | Canonical Virtualized Android comes to Anbox Cloud | Canonical Template: Streamlining open source design contributions | Canonical Beyond Mythos: responding to a new threat landscape | Canonical A look into Ubuntu Core 26: Building a local AI inference appliance in a virtual machine | Canonical This year we celebrate a decade of Ubuntu Server support on the s390x architecture: marking a long-standing collaboration between Canonical and IBM that began at LinuxCon 2015. The first release happened on April 21, 2016, bringing Ubuntu 16.04 LTS (Xenial Xerus) to IBM Z and IBM LinuxONE platforms.  A first for Ubuntu on IBM That […] AI at the edge: simplifying infrastructure with Cisco and Canonical | Canonical The next era of telco clouds: get open infrastructure choice with Sylva and Canonical Kubernetes | Canonical What is RDMA over Converged Ethernet (RoCE)? | Canonical Beyond tokens per watt – using Ubuntu 26.04 LTS for AI Beyond tokens per watt – using Ubuntu 26.04 LTS for AI | Canonical A look into Ubuntu Core 26: Deploying AI models on Renesas RZ/V series for production | Canonical RISC-V profiles – why is RVA23 significant? | Canonical AI with AMD ROCm on Ubuntu: your questions answered | Canonical When distributed workloads stall because nodes cannot exchange small messages quickly and consistently, the network is the limiting factor. How do you solve that problem? InfiniBand offers one solution. 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Run NVIDIA Nemotron 3 Nano Omni locally in a single command | Canonical
Canonical (C · 2026-04-29 · via Blog

Today, NVIDIA introduced the NVIDIA Nemotron™ 3 Nano Omni, a highly-efficient multimodal model designed to understand and reason across video, audio, images, and language. 

Canonical is enabling immediate access to Nemotrom 3 Nano Omni through inference snaps: pre-packaged AI inference runtimes distributed as snap packages for consistent deployment across systems. Developers and enterprises can deploy the model seamlessly across NVIDIA-enabled environments with a single command:

sudo snap install nemotron-3-nano-omni

With the Nemotron 3 Nano Omni delivered through inference snaps, deployment shifts from a complex integration task to a repeatable, standardized operation. A single install produces a consistent, production-grade runtime that scales across environments without rework, enabling teams to focus on building and operating agentic applications rather than managing infrastructure.

What is Nemotron 3 Nano Omni?

NVIDIA Nemotron 3 Nano Omni is an open multimodal foundation model that unifies reasoning across text, images, video, audio, and documents within a single architecture. It features a 256K token context window and a hybrid mixture of experts (MoE) architecture optimized for high multimodal throughput and accuracy. 

Nemotron 3 Nano Omni powers perception sub-agents, giving agentic systems “eyes and ears” while maintaining a unified multimodal context across steps. There is no need to stitch together separate vision, speech, and language models, reducing latency and orchestration complexity.

Easy deployment with inference snaps

Inference snaps bundle models, dependencies, and execution environments so inference workloads can run reproducibly on edge devices, workstations or servers – without manual setup.

Canonical inference snaps  provide a direct path from local installation to a production deployment. To get started, simply run:

sudo snap install nemotron-3-nano-omni

This installs a fully packaged, production-ready inference stack, including the model, runtime, and optimizations; no manual configuration required.

Inference snaps provide:

  • Zero-friction deployment: no dependency resolution, no environment drift, no custom build pipelines
  • Consistent runtime across environments: identical behavior on cloud, on-premises, and edge systems
  • Secure, confined execution: strict isolation with automatic updates and verified distribution
  • Optimized performance out of the box: pre-tuned for supported hardware
  • Simplified operations: standardized packaging reduces maintenance, patching, and upgrade complexity

For enterprises, this translates into significantly faster deployment times, saving weeks of integration and validation work, and enabling scalable AI infrastructure with a single portable artifact. 

Learn more at: https://github.com/canonical/inference-snaps 

About Canonical 

Canonical, the publisher of Ubuntu, provides open source security, support, and services. Our portfolio covers critical systems, from the smallest devices to the largest clouds, from the kernel to containers, from databases to AI. With customers that include top tech brands, emerging startups, governments and home users, Canonical delivers trusted open source for everyone. 

Learn more at https://canonical.com/ 

Learn more

Find out more about Canonical’s collaboration with NVIDIA.

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