Run NemoClaw with a Local LLM

Basic idea

NVIDIA NemoClaw is an open-source reference stack that simplifies running OpenClaw always-on assistants more safely. It installs the NVIDIA OpenShell runtime — an environment designed for executing agents with additional security — and connects them to local vLLM inference on your hardware platform. A single installer command (nemoclaw.sh) handles Node.js, OpenShell, and the NemoClaw CLI; the onboard wizard (or Express Install when offered) then creates a sandboxed agent, optional Brave Search, optional messaging channels (Telegram, Discord, or Slack), and a policy tier with network presets.

By the end of this playbook you will have a working AI agent inside an OpenShell sandbox, reachable through the Web UI or terminal TUI, with inference routed to local vLLM on your hardware platform. You can optionally add Telegram (and optional web search) — all without exposing your host filesystem or network beyond what you explicitly allow in policy.

What you'll accomplish

• Install NemoClaw with one command (nemoclaw.sh), which pulls Node.js, OpenShell, and the CLI as needed
• Complete Express Install (when offered) or walk through nemoclaw onboard with recommended settings
• Open the Web UI to interact with the agent
• Optionally enable Brave Search after onboarding
• Optionally set up Telegram (or another messaging channel) — see Instructions, optional section at the bottom
• Cleanup and uninstall with the documented uninstall flags when finished

What to know before starting

Required:

• Basic use of the Linux terminal and SSH
• Familiarity with Docker (permissions, docker run, optional docker group membership)
• Awareness of the security and risk sections below
• sudo access on the hardware platform (passwordless or interactive) — the installer and several troubleshooting steps require root privileges

Optional:

• Basic networking and SSH between nodes (multi-node capable hardware only)

Supported hardware platforms

Use the matrix below to confirm your hardware platform, OS, memory, and whether multi-node applies. The same base NemoClaw workflow applies across supported hardware platforms. Multi-node inference requires multi-node capable hardware.

Prerequisites

Hardware requirements

• Supported hardware platform — see Supported hardware platforms matrix above
• Keyboard and monitor attached, or SSH access
• Sufficient storage for the model download, vLLM container, and temporary download space (large Express models can require hundreds of GB)
• Multi-node capable hardware: validated fabric connectivity between nodes (see the Multi-node tab)

Software requirements

• Fresh install of DGX OS with latest updates (or equivalent supported OS on your hardware platform)
• Docker installed and running
• Network access to download the NemoClaw installer, container images, and model weights

Verify your system before starting:

head -n 2 /etc/os-release
nvidia-smi
docker info --format '{{.ServerVersion}}'

Expected: Ubuntu 24.04 (or your platform's supported OS), a detected NVIDIA GPU, Docker 28.x+.

Have ready before you begin

Find model recipes

NemoClaw uses local vLLM for inference. Express Install selects a maintained model for your hardware platform. Browse tested vLLM launch settings on vLLM Recipes.

Notice and disclaimers

The following sections describe safety, risks, and your responsibilities when running this demo.

Quick start safety check

Use only a clean environment. Run this demo on a fresh device or VM with no personal data, confidential information, or sensitive credentials. Keep it isolated like a sandbox.

By installing this demo, you accept responsibility for all third-party components, including reviewing their licenses, terms, and security posture. Read and accept before you install or use.

What you're getting

This experience is provided "AS IS" for demonstration purposes only — no warranties, no guarantees. This is a demo, not a production-ready solution. You will need to implement appropriate security controls for your environment and use case.

Key risks with AI agents

• Data leakage — Any materials the agent accesses could be exposed, leaked, or stolen.
• Malicious code execution — The agent or its connected tools could expose your system to malicious code or cyber-attacks.
• Unintended actions — The agent might modify or delete files, send messages, or access services without explicit approval.
• Prompt injection and manipulation — External inputs or connected content could hijack the agent's behavior in unexpected ways.

Participant acknowledgement

By participating in this demo, you acknowledge that you are solely responsible for your configuration and for any data, accounts, and tools you connect. To the maximum extent permitted by law, NVIDIA is not responsible for any loss of data, device damage, security incidents, or other harm arising from your configuration or use of NemoClaw demo materials, including OpenClaw or any connected tools or services.

Isolation layers (OpenShell)

Ancillary files

All required assets are handled by the NemoClaw installer. No manual cloning is needed for the single-node workflow.

Time & risk

• Estimated time: 30–60 MIN for a first full pass (install, onboard, model download depending on choice and network). Large Express models can add substantial download time. Optional Brave, Telegram, and cloudflared steps add time if you do them in a second session. Multi-node model download and first start can take more than an hour.
• Risk level: Medium — you are running an AI agent in a sandbox; risks are reduced by isolation but not eliminated. Use a clean environment and do not connect sensitive data or production accounts.
• Last Updated: 07/27/2026
  • Removed Agent-ready Models tab (model selection lives in Express Install); clarified Station Express recommends Nemotron 3 Ultra with DeepSeek-V4-Flash also supported; restored single upstream coding-agent starter prompt; Multi-node scoped to DGX Station