A high-performance local AI inference suite designed to run massive LLMs and creative models across Apple Silicon hardware.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mac-studio-ai
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install mac-studio-ai using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Mac Studio AI?
Mac Studio AI is a specialized framework designed to unlock the full potential of Apple Silicon for local artificial intelligence. By leveraging the massive unified memory available in Mac Studio M2, M3, and M4 Ultra configurations, this skill enables the execution of frontier models with 120B+ parameters that typically require multiple enterprise-grade GPUs. This integration through Openclaw Skills allows developers to run LLMs, image generation, and speech-to-text locally without PCIe bottlenecks.
The system utilizes the Ollama Herd architecture to turn a single device into a powerhouse or combine multiple devices into a high-availability AI fleet. This approach ensures that data stays within the local network while providing the performance needed for intensive AI research and development tasks.
Mac Studio AI Use Cases
- Running massive 120B+ parameter LLMs locally for privacy-sensitive research.
- Generating high-fidelity AI images using Flux and Stable Diffusion without cloud subscription fees.
- Building a local inference fleet by clustering multiple Mac Studio or Mac Mini devices.
- Performing secure, high-speed speech-to-text transcription for meeting records.
- Generating text embeddings for local RAG (Retrieval-Augmented Generation) applications.
How Mac Studio AI Works
- The main Mac Studio is configured as a central router that manages incoming inference requests via an OpenAI-compatible API.
- Additional Mac Studio or Mac hardware nodes connect to the router, creating a distributed compute pool.
- The system automatically discovers nodes on the local network and evaluates them based on memory, thermal state, and performance signals.
- Large models are loaded into the unified memory pool of the most capable Mac Studio in the fleet.
- Requests are intelligently routed to the appropriate node based on the specific model requirements and current system load.
- Real-time monitoring is provided through a centralized dashboard, tracking queue depths and memory utilization.
Mac Studio AI Setup
Install the core orchestration tool and start the Mac Studio router:
pip install ollama-herd
herd
To add additional nodes to your fleet, run the following on other Mac devices:
herd-node
For image generation capabilities, install the required specialized tools:
uv tool install mflux
uv tool install diffusionkit
Mac Studio AI Data Schema & Taxonomy
The skill manages its state and performance data through localized configurations and databases:
| Data Point | Description |
|---|---|
| latency.db | Stores historical performance and latency metrics for intelligent routing. |
| herd.jsonl | Structured logs for tracking requests and fleet activities. |
| Configuration | Settings for thermal thresholds and memory allocation located in the ~/.fleet-manager/ directory. |
Mac Studio AI Advanced Features
- Intelligent cross-node routing based on 7 real-time hardware signals including thermal state and available unified memory.
- Multi-model concurrency allowing different models to run simultaneously across a Mac Studio fleet.
- Automated node discovery via local network protocols for seamless horizontal scaling.
- Support for frontier-class models (up to 236B+ parameters) using quantized weights on high-memory M3 Ultra configurations.
- Local OpenAI-compatible API endpoint for easy integration with existing AI development workflows using Openclaw Skills.
SKILL.md
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