OpenClaw Hardware Requirements (2026)

What do you need to run OpenClaw?

From the 4GB minimum to the recommended 67-TOPS setup — the real specs OpenClaw needs, and the pre-configured box that skips the setup.

📅 Updated March 2026

With OpenClaw v2026.3.14 and NemoClaw from NVIDIA, hardware requirements have evolved. The minimum specs remain 4GB RAM and Node.js 20+, but for the best experience with browser automation, multi-agent workflows, and voice pipelines, we now recommend dedicated hardware with NVIDIA CUDA support. The Jetson Orin Nano remains the sweet spot — 67 TOPS of AI compute at just 15W, enough for simultaneous LLM inference, browser automation, and voice processing.

Need the recommendation, not just the specs?

This page explains minimum and recommended specs. If you want the final buying answer, read our guide to the best OpenClaw hardware, where we compare ClawBox, Raspberry Pi, Mac Mini, and other always-on AI setups. For the 2026 buying decision — mini PC vs Jetson vs Mac mini vs ClawBox, with real power costs and setup times — see our full comparison guide. Prefer measured numbers over spec-sheet claims? See the real local-LLM benchmark from a production ClawBox — 22–45 tokens/sec at under 20 watts. And if you're still wondering what OpenClaw actually is, our explainer covers the assistant itself before you pick hardware for it.

ClawBox Specifications

Everything you need to know about ClawBox hardware

🧠

AI Performance

67 TOPS

NVIDIA Jetson Orin Nano Super with dedicated AI accelerator

🎮

GPU

1024-core Ampere GPU

625 MHz base clock, 40.96 GB/s memory bandwidth

💾

Memory

8GB LPDDR5

102.4 GB/s bandwidth, unified CPU/GPU memory

📀

Storage

512GB NVMe SSD

PCIe Gen3 x4, 2,100 MB/s read speed, pre-installed

⚡

Power

7-25W

15W typical operation, 20W USB-C PD adapter included

📡

Connectivity

WiFi 6 + Bluetooth 5.0

Dual-band 802.11ax, Gigabit Ethernet port

🔌

Ports

USB-A, USB-C, HDMI, Ethernet

microSD slot, 40-pin GPIO header

📏

Size

100 × 79 × 31mm

Compact carbon color case, 260g total weight

AI Model Performance

What you can run on ClawBox

Model	Speed	Quality
Llama 3.1 8B (Q4)	~3.5 tok/s	Excellent
Mistral 7B (Q4)	~4.2 tok/s	Excellent
Phi-3 Mini (Q4)	~6.8 tok/s	Good
Gemma 2B (Q4)	~9.1 tok/s	Fast
TinyLlama 1B (Q4)	~15.3 tok/s	Basic
Qwen2.5 7B (Q4)	~4.0 tok/s	Excellent

For larger models, use BYOK with cloud APIs (Claude, GPT, Gemini).

What's Included

Hardware

✓ NVIDIA Jetson Orin Nano Super
✓ 512GB NVMe SSD (pre-installed)
✓ Carbon color case
✓ 20W USB-C power supply
✓ Ethernet & WiFi ready

Software

✓ Ubuntu 22.04 LTS
✓ OpenClaw pre-installed
✓ Browser automation ready
✓ Voice pipeline configured
✓ Free software updates

Power Requirements

7W idle

15W typical

15W

25W max

25W

Included 20W USB-C power supply is all you need.

OpenClaw Server Requirements

What a headless, always-on OpenClaw install actually needs

Running OpenClaw as a server — no monitor, just an always-on machine you reach from Telegram or WhatsApp — is how most people end up using it. The requirements are modest, but they are real: the agent keeps a browser, a Node.js runtime and often a local model warm around the clock.

Component	Minimum	Recommended
RAM	4GB	8GB unified (for local AI models)
CPU	2 cores (x86_64 or ARM64)	4+ cores, or Jetson with CUDA
Storage	20GB free	50GB+ NVMe SSD
OS & runtime	Linux with Node.js 20+	Headless Ubuntu LTS, Node.js 20+

A cheap VPS meets the minimum on paper, but shared vCPUs and burstable RAM fall short in practice: browser automation spikes the CPU, local models need real memory bandwidth, and around-the-clock uptime on rented infrastructure means your agent — and its data — live in someone else's cloud.

The pre-configured alternative: ClawBox is a 67-TOPS Jetson server with OpenClaw already installed, tuned for exactly this workload at 15W. See what ClawBox does →

Why Dedicated Hardware for OpenClaw?

Running OpenClaw on dedicated hardware vs shared VPS or your daily-use computer

✓ Dedicated Hardware

✓
24/7 uptime — your AI assistant never sleeps. Heartbeat checks, scheduled tasks, and proactive monitoring run around the clock without interruption.
✓
No resource competition — CPU, GPU, and RAM are 100% dedicated to OpenClaw. No other apps fighting for memory or causing unexpected slowdowns.
✓
Consistent performance — predictable response times for AI inference, voice processing, and browser automation. No “noisy neighbor” problems.
✓
Lower long-term cost — ClawBox at €549 one-time vs VPS at €20-40/month (€720-1,440 over 3 years). The hardware pays for itself in under 2 years.
✓
True privacy — your data stays on your physical hardware, on your network. No cloud provider has access to your conversations, files, or automations.

✗ Shared VPS / Your Laptop

✗
Downtime when you close your laptop — OpenClaw stops when your computer sleeps, restarts, or runs out of battery.
✗
Resource contention — browser tabs, Slack, VS Code all compete with OpenClaw for RAM and CPU. Performance degrades unpredictably.
✗
VPS costs add up — a GPU-capable VPS costs €40-80/month. Over 3 years that's €1,440-2,880 — far more than dedicated hardware.
✗
No local AI inference — most VPS providers don't offer GPU access. You're stuck with cloud API calls only.

The ideal dedicated hardware for OpenClaw: NVIDIA Jetson Orin Nano at just 15W.

67 TOPS of AI performance, fanless operation, always-on by design. ClawBox packages this with a 512GB NVMe SSD, carbon color case, and OpenClaw pre-installed — ready in 5 minutes.

Frequently Asked Questions

What are the minimum hardware requirements for OpenClaw?▼

OpenClaw requires at least 4GB RAM, a modern CPU (x86_64 or ARM64), Node.js 20+, and an always-on internet connection. It runs on Linux, macOS, and Windows.

What is the best hardware for OpenClaw?▼

ClawBox is the recommended hardware — NVIDIA Jetson Orin Nano 8GB with 512GB NVMe SSD, delivering 67 TOPS of AI performance at just 7-15W. It comes with OpenClaw pre-installed for €549.

Can I run OpenClaw on a Raspberry Pi?▼

Yes, OpenClaw runs on Raspberry Pi 4 (4GB+) and Pi 5. However, for AI workloads like local LLMs, a more powerful device like ClawBox with its 67 TOPS GPU is recommended.

Does OpenClaw require a GPU?▼

No, OpenClaw works without a GPU for basic assistant features. For local AI model inference, a GPU or NPU significantly improves performance. ClawBox includes a 67 TOPS NVIDIA GPU.

What is the best device for OpenClaw?▼

ClawBox is the best dedicated device for OpenClaw. It features an NVIDIA Jetson Orin Nano 8GB with 67 TOPS AI performance, 512GB NVMe SSD, and comes with OpenClaw pre-installed for €549. It runs 24/7 at just 7-15W. Alternatives include Mac Mini (more expensive, no GPU acceleration) or a Linux PC with an NVIDIA GPU.

What are the OpenClaw system requirements for local AI models?▼

For running local AI models with OpenClaw, you need at least 8GB RAM, an NVIDIA GPU with 4GB+ VRAM (or Jetson with unified memory), and 50GB+ storage. ClawBox meets all these requirements out of the box with its 8GB unified GPU memory, 67 TOPS performance, and 512GB NVMe SSD.

Can I build my own computer for OpenClaw instead of buying ClawBox?▼

Yes, OpenClaw runs on any Linux, macOS, or Windows machine with Node.js 20+. However, building a comparable always-on AI setup typically costs more: a mini PC ($300-500) plus GPU ($200-400) plus SSD plus power costs ($15-30/month). ClawBox at €549 includes everything pre-configured and runs at just 15W (~€3/month electricity).

What is the best mini PC for OpenClaw?▼

For a mini PC setup, the NVIDIA Jetson Orin Nano is the best choice due to its 67 TOPS GPU acceleration at only 7-15W. The Mac Mini M4 works but costs more ($599+) and lacks dedicated AI acceleration. Intel NUCs and AMD mini PCs work for basic features but can't run local AI models efficiently without a discrete GPU.

What hardware do I need to run OpenClaw?▼

You need a machine with at least 4GB RAM, a modern dual-core x86_64 or ARM64 CPU, 20GB of free storage, Node.js 20+, and an always-on internet connection. Any mini PC, home server, or NVIDIA Jetson meets this. For local AI models, step up to 8GB RAM and a CUDA-capable GPU — or get ClawBox, which ships pre-configured with 67 TOPS at 15W for €549.

What are the OpenClaw server requirements?▼

For a headless OpenClaw server install: 4GB RAM minimum (8GB recommended), 2+ CPU cores, 20GB storage (50GB+ NVMe recommended for local models), and Linux with Node.js 20+. A small VPS can run the basics, but browser automation and local AI inference quickly exhaust shared vCPUs and burstable RAM — dedicated hardware like ClawBox avoids those limits at 15W.

What do I need to run OpenClaw?▼

To run OpenClaw you need: 4GB+ RAM (8GB for local AI models), a modern x86_64 or ARM64 CPU, Node.js 20+, and an always-on internet connection. For local AI inference you also want a GPU or NPU with CUDA support. The simplest option is ClawBox — a €549 NVIDIA Jetson box that ships with everything pre-installed and runs OpenClaw 24/7 in 5 minutes, no setup.

How big is OpenClaw / the ClawBox?▼

OpenClaw itself is lightweight software (a few hundred MB) that runs on small hardware. The ClawBox device is compact — about the size of a paperback book — based on the NVIDIA Jetson Orin Nano, fanless, drawing just 7-15W, so it sits quietly on a desk or shelf and runs OpenClaw around the clock.

Best OpenClaw Hardware →Best Hardware Comparison →ClawBox vs Mac Mini →OpenClaw on Raspberry Pi →OpenClaw on Windows →OpenClaw Tutorial →Setup Guide →Pricing Breakdown →

Ready to Get Started?

ClawBox comes with everything you need — pre-installed, pre-configured, ready in 5 minutes.

30-day money-back guarantee · Ships to 30+ countries · DHL Express