NemoClaw Windows Setup Guide

NemoClaw does not run on Windows natively. It relies on Linux kernel features like Landlock, seccomp, and network namespaces — none of which exist on Windows. Even experienced developers have struggled to get it working, and the official documentation only supports Ubuntu 22.04 or later.

But there is a way. By using WSL2 (Windows Subsystem for Linux), you can run a full Ubuntu environment inside Windows and install NemoClaw inside that. This guide walks you through every step — from installing WSL2 and Docker Desktop, to setting up NVIDIA GPU passthrough (the step most guides skip), to running the NemoClaw installer and getting your first agent response.

We also cover the common repo errors you’ll likely hit along the way and how to fix them. All commands are single-line and copy-paste friendly — no backslashes, no multi-line pipes. If you prefer to watch instead of read, the full video walkthrough is linked below.

Step 1: Install WSL2 with Ubuntu

PowerShell (Admin):

wsl --install -d Ubuntu-22.04

After restart, in Ubuntu:

sudo apt update && sudo apt upgrade -y

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Step 2: Enable systemd

sudo nano /etc/wsl.conf

Add:

[boot] systemd=true

PowerShell:

wsl --shutdown

Reopen Ubuntu, verify:

systemctl is-system-running

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Step 3: Docker Desktop

1. Install Docker Desktop for Windows: https://www.docker.com/products/docker-desktop/
2. Settings → Resources → WSL Integration → toggle on Ubuntu → Apply & Restart

Verify in Ubuntu:

docker run hello-world

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Step 4: NVIDIA GPU passthrough

1. Install latest Windows NVIDIA driver: https://www.nvidia.com/Download/index.aspx
2. Do NOT install a Linux NVIDIA driver inside WSL2

In Ubuntu — add signing key:

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg

Add repo (use the .list file URL, not the bare directory):

curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

Install:

sudo apt update sudo apt install -y nvidia-container-toolkit sudo nvidia-ctk runtime configure --runtime=docker

Restart Docker Desktop, then:

sudo apt install -y nvidia-cuda-toolkit

Verify (both must work):

nvidia-smi nvcc --version

If nvidia-smi fails → update Windows NVIDIA driver → wsl —shutdown → retry.

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Step 5: Node.js 20+

curl -fsSL https://deb.nodesource.com/setup_20.x | sudo -E bash - sudo apt install -y nodejs node -v && npm -v

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Step 6: Install NemoClaw (CLI + onboard wizard)

curl -fsSL https://nvidia.com/nemoclaw.sh | bash

The wizard runs automatically through [1/7] to [7/7]:

• [4/7] — Enter your NVIDIA API key from https://build.nvidia.com
• [5/7] — Choose cloud model (default: nemotron-3-super-120b-a12b)
• [7/7] — Accept suggested policy presets (pypi, npm) by pressing Y

After it finishes:

source ~/.bashrc nemoclaw --version openshell --version

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Step 7: Connect and test

Check sandbox status

nemoclaw (sandbox name) status

Connect:

nemoclaw (sandbox name) connect

Inside the sandbox, launch chat:

openclaw tui

Or test via CLI:

openclaw agent --agent main --local -m "hello" --session-id test

Exit sandbox:

exit

Check logs if anything feels off:

nemoclaw boxplant logs --follow

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Step 8: Harden WSL2

sudo nano /etc/wsl.conf

Full config:

[boot] systemd=true [interop] enabled=false appendWindowsPath=false [automount] enabled=false

PowerShell:

wsl --shutdown

Optional — memory limit (create %UserProfile%.wslconfig):

[wsl2] memory=12GB swap=8GB

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Daily Use

nemoclaw (sandbox name) connect openclaw tui

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Nuclear Reset (if things break)

openshell sandbox delete (sandbox name) openshell gateway destroy --name nemoclaw docker volume rm openshell-cluster-nemoclaw

Then rerun curl -fsSL https://nvidia.com/nemoclaw.sh | bash from Step 6.

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Manual Workaround (only if Step 6 wizard fails with sandbox errors)

bash openshell sandbox delete my-sandbox 2>/dev/null openshell gateway destroy --name nemoclaw 2>/dev/null docker volume rm openshell-cluster-nemoclaw 2>/dev/null openshell gateway start --name nemoclaw openshell status openshell provider create --name nvidia-nim --type nvidia --credential NVIDIA_API_KEY=nvapi-YOUR_KEY_HERE openshell inference set --provider nvidia-nim --model nvidia/nemotron-3-super-120b-a12b openshell sandbox create --name my-sandbox --from openclaw openshell sandbox ssh my-sandbox openclaw onboard

When prompted for provider → select Custom Provider → enter https://inference.local/v1

If Anthropic key is set: unset ANTHROPIC_API_KEY