apple-silicon
Apple Silicon Monitor Top.
mactop is a terminal-based monitoring tool "top" designed to display real-time metrics for Apple Silicon chips written by Carsen Klock. It provides a simple and efficient way to monitor CPU and GPU usage, E-Cores and P-Cores, power consumption, GPU frequency, temperatures, and other system metrics directly from your terminal
The free AI already on your Mac.
macOS Tahoe ships with a 3B parameter LLM. apfel gives you CLI access with one brew install. No model downloads, no API keys, no configuration needed, just works.
Related contents:
Hold-to-talk speech-to-text for macOS. 100% local, powered by WhisperKit and local LLM cleanup. Hold Control to record, release to transcribe and paste.
A second brain for the AI era. Free forever.
Organize your notes as Markdown files. With native relationships, Git, and Claude Code integration.
Cost-efficient private AI inference. Private Inference Network on Idle Macs.
Darkbloom routes encrypted requests to hardware-verified Apple Silicon providers, delivering comparable model performance at about 50% lower cost than typical API providers. Prompts stay hidden from operators, and Mac owners earn from compute they already own.
LLM inference, optimized for your Mac. Local AI, no more waiting on your Mac.
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar.
macOS-native MLX server with smart caching. Claude Code, OpenClaw, and Cursor respond in 5 seconds, not 90.
Related contents:
macOS & Linux Containers for Computer-Use AI Agents on Apple Silicon. Run Docker Containers for Computer-Use AI Agents on Apple Silicon.
TL;DR: c/ua (pronounced "koo-ah", short for Computer-Use Agent) is a framework that enables AI agents to control full operating systems within high-performance, lightweight virtual containers. It delivers up to 97% native speed on Apple Silicon and works with any vision language models.
container is a tool that you can use to create and run Linux containers as lightweight virtual machines on your Mac. It's written in Swift, and optimized for Apple silicon.
The tool consumes and produces OCI-compliant container images, so you can pull and run images from any standard container registry. You can push images that you build to those registries as well, and run the images in any other OCI-compliant application.
Related contents:
DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm.
DwarfStar is a small native inference engine optimized first for DeepSeek V4 Flash. It also supports GLM 5.2 and, on very high-memory machines, DeepSeek V4 PRO. It is self-contained and deliberately narrow, not a general GGUF runner. Model loading, prompt rendering, tool calls, KV state, the HTTP server, and the coding agent are built and tested together. The repository also includes tools and data for GGUF, imatrix, quality, and speed.
Containerization is a Swift package for running Linux containers on macOS.
The Containerization package allows applications to use Linux containers. Containerization is written in Swift and uses Virtualization.framework on Apple silicon.
Gemma 4 26B-A4B inference in about 2 GB of RAM A custom Swift + Metal runtime for any Apple Silicon Mac, even the 8 GB ones.
Install the AWS CLI on modern Macs without a package manager.
Related contents:
llama.cpp fork with TurboQuant optimization
Related contents:
Free Up Tens to Hundreds of GB on Your Mac
Trim universal binaries from your audio plugins. If you're on Apple Silicon, you're only using half the code. Get that space back.
Related contents:
An array framework for Apple silicon.
MLX is an array framework for machine learning research on Apple silicon, brought to you by Apple machine learning research.
Run LLMs Locally on Apple Silicon, Fast.
The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing. Drop-in OpenAI replacement. Works with Claude Code, Cursor, Aider.
Related contents:
The future of on device AI. Deploy high-performance AI directly in your app — with zero latency, full data privacy, and no inference costs.
Uzu is a high-performance inference engine for AI models on Apple Silicon.
R interface to Apple’s MLX (Machine Learning eXchange) library.
Rmlx provides an R interface to Apple’s MLX framework, enabling high-performance GPU computing on Apple Silicon.