一键部署
独立龙虾One-touch OpenClaw Install
快速在Arm设备上运行
多个独立OpenClaw应用Run multiple independent OpenClaw apps on your Arm device
On your Arm device terminal
Core Features
AI application infrastructure built for Arm devices
One-Click Deploy
No manual environment setup. Jishu handles everything — get running in minutes
Capability Integration
Scan to connect WeChat, Feishu — quickly use various Skills, MCP and rich tools
Security Sandbox
Container-based isolation for Claw apps and system environment, independent API Key management, selective data authorization
Multi-Instance
Run multiple Claw instances in parallel on a single device, fully utilizing hardware capabilities
Unified Management
Centrally manage versions, configs, and status of all AI apps from a single interface
Why Not PC or Cloud?
Only standalone Arm devices running Lobster deliver the best experience
- Independence: PCs serve multiple purposes — work and life data interfere with each other
- Environment: Complex Windows desktop limits Lobster capabilities, must stay awake
- Power: 5W vs 100W+ (Raspberry Pi 5 ~$70, PC costs hundreds) — significant difference for 24/7 operation
- Security: All data uploaded to cloud — leak and abuse risks
- Design: Contradicts standalone AI principle of local data, local execution — not private deployment
- Experience: Higher network latency, IPs flagged as server not personal — web access restricted
- As local computing power improves, data interaction and Agent execution can be powered by local GPU/NPU, enabling fully offline operation and ensuring data privacy
- Connect cameras, wheels, limbs, and sensors to turn your Arm device into a truly perceptive, actionable embodied AI terminal
Supported Hardware
Hardware: Raspberry Pi 5 or equivalent — 4-core Arm Cortex-A76+, 4GB RAM, 16GB storage OS: Ubuntu 22.04+, Debian 12+, MacOS 26
Raspberry Pi 5
BCM2712 · 4×Cortex-A76 · 4/8GB
Affordable, mature ecosystem — ideal for running standalone AI apps
Minimum: Cortex-A76 quad-core or above + 4GB RAM
Nvidia Jetson Orin / Thor
Cortex-A78AE / Neoverse-V3AE · 4~128GB
Native Nvidia GPU integration — supports local model inference at varying scales
Ref: Jetson Orin Nano · Jetson AGX Orin · Jetson Thor T4000/T5000
Mac Mini / Studio
Coming SoonApple Silicon M1~M5 · Unified Memory 8~192GB
Apple unified memory architecture — peak local inference, top choice for multi-instance on a single device
Rockchip RK3588
4×Cortex-A76 + 4×Cortex-A55 · up to 32GB
Cost-effective domestic edge chip, 6 TOPS NPU, octa-core big.LITTLE architecture
Ref board: Firefly EC-I3588J
CIX P1
8×Cortex-A720 + 4×Cortex-A520 · up to 64GB
Domestic high-performance Arm SoC, ARMv9.2 cores, with 30 TOPS "Zhouyi" NPU
Ref board: Radxa Orion O6
Huixi Guangzhi R1
24×Cortex-A78AE · 32~128GB
Domestic automotive-grade high-performance AI chip, 500 TOPS Rhino NPU
Mediatek Genio720
2×Cortex-A78 + 6×Cortex-A55 · up to 16GB
Leading AIoT chip, 6nm process, 10 TOPS NPU, Antutu score up to 800K
Ref board: Zelustek G720 development board
More Arm SoCs under evaluation — other chips and devices are welcome to try, stay tuned for announcements
Coming SoonEarly Partners
Welcome to join and co-build the ecosystem
Business: bd@aijishu.com
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