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.

ClawBox 仕様

ボックスの中身は？

67 TOPSのAI性能、8GBメモリ、512GBストレージを備えたNVIDIA Jetson Orin Nano Super。

📅 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.

完全な仕様

ClawBoxハードウェアについて知っておくべきすべて

🧠

AI性能

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

💾

メモリ

8GB LPDDR5

102.4 GB/s bandwidth, unified CPU/GPU memory

📀

ストレージ

512GB NVMe SSD

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

⚡

消費電力

7-25W

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

📡

接続性

WiFi 6 + Bluetooth 5.0

Dual-band 802.11ax, Gigabit Ethernet port

🔌

ポート

USB-A, USB-C, HDMI, Ethernet

microSD slot, 40-pin GPIO header

📏

サイズ

100 × 79 × 31mm

Compact carbon fiber case, 260g total weight

AIモデル性能

ClawBoxで実行できるもの

モデル	速度	品質
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

大規模なモデルには、クラウドAPI（Claude、GPT、Gemini）でのBYOKをご利用ください。

同梱内容

ハードウェア

✓ NVIDIA Jetson Orin Nano Super
✓ 512GB NVMe SSD（プリインストール済み）
✓ カーボンファイバーケース
✓ 20W USB-C 電源アダプター
✓ イーサネット＆WiFi 対応

ソフトウェア

✓ Ubuntu 22.04 LTS
✓ OpenClaw プリインストール済み
✓ ブラウザ自動化対応済み
✓ 音声パイプライン設定済み
✓ 無料ソフトウェアアップデート

電力要件

アイドル時7W

通常15W

15W

最大25W

25W

付属の20W USB-C 電源アダプター一つで十分です。

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 fiber case, and OpenClaw pre-installed — ready in 5 minutes.

Ready to Get Started?

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

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