Best VPS for NemoClaw: Run Secure AI Agents on Your Server

Want an always-on AI agent that respects your privacy? NemoClaw is NVIDIA’s open-source stack that wraps OpenClaw with enterprise-grade security guardrails — and a GPU VPS is one of the best ways to run it.

What is NemoClaw?

NemoClaw is an open-source stack from NVIDIA that enhances OpenClaw with privacy and security controls. It lets you deploy self-evolving, always-on AI assistants with a single command.

Think of it this way: OpenClaw gives you a personal AI assistant across WhatsApp, Telegram, and Discord. NemoClaw adds a security layer on top — policy-based guardrails that control how your agent behaves, what data it can access, and how it communicates with cloud models.

What NemoClaw Adds Over OpenClaw

• Privacy router — Routes agent requests through guardrails before hitting cloud models
• NVIDIA OpenShell — Enforces policy-based security rules on agent behavior
• Local model support — Run NVIDIA Nemotron models on your own hardware
• Smart compute routing — Evaluates available resources and picks the best model automatically
• Skill learning — Agents develop new capabilities through cloud-based frontier models, within your security policies

Why Self-Host NemoClaw?

• Privacy-first AI — Your data stays on your server, guardrails prevent leaks
• Always-on agents — 24/7 autonomous operation, even when your PC is off
• Full control — Define exactly what your agent can and can’t do
• No vendor lock-in — Open-source, run anywhere with NVIDIA GPUs
• Cost predictable — Fixed VPS cost vs unpredictable API bills

Honest Take: Local NVIDIA Hardware Is Ideal

Before we get into VPS picks, let’s acknowledge the elephant in the room — NemoClaw was designed for local NVIDIA hardware.

NVIDIA lists these as supported platforms:

• GeForce RTX PCs and laptops
• RTX PRO workstations
• DGX Station
• DGX Spark

If you already own an NVIDIA GPU, running NemoClaw at home is the cheapest path. A desktop with an RTX 4070 draws about 30W idle and handles NemoClaw without breaking a sweat.

When a GPU VPS makes more sense:

• You don’t own NVIDIA hardware (and don’t want to buy any)
• You need guaranteed uptime without power outage risks
• You want your AI agent accessible from anywhere without port forwarding
• You need to scale beyond a single GPU
• You’re running a team setup where multiple people use the agent

For those cases, a GPU VPS gives you the NVIDIA hardware NemoClaw needs without the upfront cost.

NemoClaw VPS Requirements

NemoClaw needs NVIDIA GPU compute. CPU-only VPS won’t work for the full stack.

Requirement	Minimum	Recommended
GPU	NVIDIA with 8GB VRAM	NVIDIA with 16GB+ VRAM
CPU	4 vCPU	8+ vCPU
RAM	16GB	32GB+
Storage	50GB NVMe	100GB+ NVMe
OS	Ubuntu 22.04+	Ubuntu 24.04 LTS
CUDA	12.0+	12.4+

The GPU requirement is non-negotiable — NemoClaw relies on NVIDIA’s software stack (CUDA, TensorRT) for local model inference.

Top GPU VPS Picks for NemoClaw

1. Vultr Cloud GPU (Best Availability)

$90/mo | NVIDIA A16 (16GB VRAM), 6 vCPU, 16GB RAM

Vultr has the most accessible GPU instances among mainstream providers:

• NVIDIA A16 with 16GB VRAM — handles Nemotron models well
• Hourly billing if you want to test first
• Global data centers
• Simple API for automation

Why it’s great for NemoClaw: Easy to provision, no long-term commitment, and enough VRAM for medium-sized models with the security stack running alongside.

2. Hetzner Dedicated GPU (Best Value)

€179/mo | NVIDIA RTX 4000 (8GB VRAM), 8 cores, 64GB RAM

If you need always-on NemoClaw, Hetzner’s dedicated GPU servers are hard to beat:

• Fixed monthly pricing — no surprise bills
• 64GB system RAM for large context windows
• Unmetered traffic
• German data centers (GDPR compliant)

Trade-off: 8GB VRAM limits you to smaller Nemotron models, but the 64GB system RAM compensates with offloading.

3. Lambda Labs (Best for AI Workloads)

$0.50/hr (~$360/mo) | NVIDIA A10 (24GB VRAM)

Lambda specializes in AI infrastructure:

• 24GB VRAM runs larger Nemotron and open models
• Pre-installed CUDA and ML frameworks
• Purpose-built for AI workloads

Best for: Teams that need full Nemotron model performance without quantization compromises.

4. RunPod (Cheapest Entry Point)

$0.20/hr | NVIDIA RTX 4090 (24GB VRAM)

RunPod’s spot pricing makes it the cheapest way to try NemoClaw:

• 24GB VRAM at a fraction of the cost
• Community cloud and secure cloud options
• Template marketplace for quick setup

Caveat: Spot instances can be interrupted. Use secure cloud for production agents.

How to Install NemoClaw on a GPU VPS

Step 1: Provision Your GPU VPS

Pick a provider above, select Ubuntu 24.04, and make sure NVIDIA drivers are pre-installed (most GPU VPS providers include them).

# Verify GPU is detected
nvidia-smi

# Should show your GPU model and CUDA version

Step 2: Install NemoClaw

# One-command install
curl -fsSL https://nvidia.com/nemoclaw.sh | bash

This installs the full stack: OpenClaw, NVIDIA OpenShell, privacy router, and local model support.

Step 3: Run Onboarding

nemoclaw onboard

The wizard guides you through:

• Configuring security policies and guardrails
• Setting up model authentication (cloud and local)
• Defining privacy rules for data handling
• Installing the background service

Step 4: Connect Messaging Channels

NemoClaw inherits OpenClaw’s multi-platform support:

Telegram:

openclaw channels add --channel telegram --token "YOUR_BOT_TOKEN"

WhatsApp:

openclaw channels login

Discord:

openclaw channels add --channel discord --token "YOUR_BOT_TOKEN"

Step 5: Verify Security Guardrails

# Check that OpenShell policies are active
nemoclaw status

# Test a guardrail violation (should be blocked)
nemoclaw test --policy privacy

NemoClaw vs OpenClaw: Which Should You Run?

Feature	OpenClaw	NemoClaw
AI Assistant	Yes	Yes
Messaging Integration	Yes	Yes
Security Guardrails	Basic	Policy-based (OpenShell)
Privacy Router	No	Yes
Local NVIDIA Models	No	Yes (Nemotron)
GPU Required	No	Yes
Min VPS Cost	~$5/mo	~$90/mo
Best For	Personal assistant	Privacy-critical agents

Bottom line: If you just want a personal AI assistant and privacy isn’t a top concern, OpenClaw on a $5 VPS is the simpler choice. If you need enforced security policies, local model inference, and privacy guardrails, NemoClaw is worth the GPU cost.

Security Configuration Tips

1. Define Data Classification Policies

NemoClaw’s OpenShell lets you classify data and set rules:

• What data can be sent to cloud models
• What stays on-device only
• Which tools agents can access

2. Lock Down Network Access

# Firewall: only allow what's needed
ufw allow ssh
ufw allow 443/tcp   # For cloud model API calls
ufw deny 11434/tcp  # Block external Ollama access
ufw enable

3. Enable Audit Logging

# Monitor agent behavior
journalctl -u nemoclaw -f

# Review guardrail enforcement
nemoclaw logs --filter policy-violations

4. Rotate API Keys

Set up key rotation for cloud model providers to limit exposure if a key leaks.

Cost Comparison

Setup	Monthly Cost	Privacy Level	Performance
OpenClaw on Hostinger	$5/mo	Medium (cloud models)	Good
NemoClaw on Vultr GPU	$90/mo	High (guardrails + local)	Fast
NemoClaw on Lambda	$360/mo	High	Fastest
NemoClaw at home (RTX 4070)	$10/mo electricity	Highest	Fast

FAQ

Does NemoClaw require an NVIDIA GPU?

Yes. NemoClaw uses NVIDIA’s software stack (CUDA, TensorRT, Nemotron models) for local inference. CPU-only setups won’t work for the full feature set. If you don’t need NVIDIA-specific features, use OpenClaw instead.

Can I use NemoClaw with cloud models only?

You can route requests through cloud models, but the privacy router and local inference are the whole point. Without a GPU, you lose NemoClaw’s core value proposition.

Is NemoClaw free?

Yes, it’s open-source. You only pay for the GPU VPS (or electricity if running at home).

How does the privacy router work?

The privacy router sits between your agent and cloud models. It evaluates each request against your security policies, strips sensitive data before sending to cloud APIs, and routes appropriate requests to local Nemotron models instead.

Can I run NemoClaw and Ollama together?

Yes. NemoClaw supports local models through Nemotron, but you can also connect it to an Ollama instance for additional open-source models. Just make sure you have enough VRAM for both.

Conclusion

For self-hosting NemoClaw, Vultr Cloud GPU at $90/mo offers the best balance of cost, availability, and VRAM. That gives you a fully secured AI agent with privacy guardrails running 24/7.

If budget allows, Lambda’s A10 instances ($360/mo) provide the headroom for larger Nemotron models without quantization trade-offs. And if you already own NVIDIA hardware, running NemoClaw at home remains the most private and cost-effective option.

For a simpler setup without GPU requirements, check out OpenClaw on a budget VPS. For broader AI hosting needs, see our LLM hosting guide and AI inference comparison.