OpenClaw 硬件要求 (2026)

运行 OpenClaw 需要什么?

从 4GB 最低门槛到推荐的 67 TOPS 配置 — OpenClaw 真正需要的硬件规格，以及帮你跳过安装环节的预配置主机。

📅 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规格

了解ClawBox硬件的全部信息

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AI性能

67 TOPS

NVIDIA Jetson Orin Nano Super with dedicated AI accelerator

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GPU

1024-core Ampere GPU

625 MHz base clock, 40.96 GB/s memory bandwidth

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内存

8GB LPDDR5

102.4 GB/s bandwidth, unified CPU/GPU memory

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存储

512GB NVMe SSD

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

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功率

7-25W

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

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连接性

WiFi 5 + Bluetooth 5.0

Dual-band 802.11ac, Gigabit Ethernet port

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端口

USB-A, USB-C, HDMI, Ethernet

microSD slot, 40-pin GPIO header

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尺寸

100 × 79 × 31mm

Compact carbon color case, 260g total weight

AI 模型性能

您可以在 ClawBox 上运行的内容

模型	速度	质量
Llama 3.2 1B (Q4)	~45 tok/s	Fast
Gemma 2 2B (Q4)	~26 tok/s	Good
Qwen2.5 3B (Q4)	~23 tok/s	Excellent
Phi-3 Mini 3.8B (Q4)	~22 tok/s	Excellent
7–8B class (Q4)	~10 tok/s	Tight fit

对于较大的模型, 请使用带云API的BYOK(自带密钥)(Claude, GPT, Gemini).

包含内容

硬件

✓ NVIDIA Jetson Orin Nano超级版
✓ 512GB NVMe SSD (预安装)
✓ 碳色外壳
✓ 20W USB-C 电源适配器
✓ 以太网和WiFi就绪

软件

✓ Ubuntu 22.04 LTS
✓ OpenClaw 预安装
✓ 浏览器自动化就绪
✓ 语音管道已配置
✓ 免费软件更新

功耗要求

7W 待机

15W 典型值

15W

25W 最大值

25W

附带的20W USB-C电源适配器即可满足您的需求。

OpenClaw 服务器要求

一台无头 (headless)、全天候在线的 OpenClaw 服务器到底需要什么

把 OpenClaw 当作服务器来跑 — 不接显示器，只留一台常开的机器，通过 Telegram 或 WhatsApp 随时召唤 — 这是大多数人最终的使用方式。要求不高，但确实存在：智能体会让浏览器、Node.js 运行时，以及往往还有一个本地模型，全天候保持待命。

组件	最低	推荐
RAM	4GB	8GB 统一内存 (用于本地 AI 模型)
CPU	2 核 (x86_64 或 ARM64)	4 核以上，或带 CUDA 的 Jetson
存储	20GB 可用空间	50GB+ NVMe SSD
系统与运行时	Linux 加 Node.js 20+	无头 Ubuntu LTS，Node.js 20+

便宜的 VPS 账面上够到了最低要求，但共享 vCPU 和突发型 RAM 在实际使用中并不够：浏览器自动化会让 CPU 瞬间打满，本地模型需要真正的内存带宽，而在租来的基础设施上全天候运行，意味着你的智能体 — 连同它的数据 — 都住在别人的云里。

预配置的替代方案：ClawBox 是一台 67 TOPS 的 Jetson 服务器，出厂即装好 OpenClaw，专为这类工作负载调校，功耗仅 15W。看看 ClawBox 能做什么 →

Why Dedicated Hardware for OpenClaw?

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

✓ Dedicated Hardware

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24/7 uptime — your AI assistant never sleeps. Heartbeat checks, scheduled tasks, and proactive monitoring run around the clock without interruption.
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No resource competition — CPU, GPU, and RAM are 100% dedicated to OpenClaw. No other apps fighting for memory or causing unexpected slowdowns.
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Consistent performance — predictable response times for AI inference, voice processing, and browser automation. No “noisy neighbor” problems.
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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.
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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

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Downtime when you close your laptop — OpenClaw stops when your computer sleeps, restarts, or runs out of battery.
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Resource contention — browser tabs, Slack, VS Code all compete with OpenClaw for RAM and CPU. Performance degrades unpredictably.
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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.
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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.

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