Lume – OS lightweight CLI for MacOS and Linux VMs on Apple Silicon
We just open-sourced Lume - a tool we built after hitting walls with existing virtualization options on Apple Silicon. No GUI, no complex stacks - just a single binary that lets you spin up macOS or Linux VMs via CLI or API. Why we built Lume: - Run native macOS VMs in 1 command, using Apple Virtualization.Framework: `lume run macos-sequoia-vanilla:latest` - Prebuilt images on https://ghcr.io/trycua (macOS, Ubuntu on ARM) - API server to manage VMs programmatically `POST /lume/vms` - A python SDK on github.com/trycua/pylume Run prebuilt macOS images in just…
Lume – OS lightweight CLI for MacOS and Linux VMs on Apple Silicon launched on February 2, 2025 with 309 votes, #105 of 5,999 launches that month and more than 99% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Lume is a lightweight command-line tool for spinning up macOS and Linux virtual machines on Apple Silicon Macs and Linux VMs. It uses Apple's Virtualization Framework to launch native macOS instances with a single command, offering prebuilt images and an API server for programmatic VM management. Developers can use it directly via CLI or through a Python SDK, making it an alternative to more complex virtualization solutions.
written from the facts on this page · September 2026
From the sources
Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation. - trycua/cua
In the maker’s words, at launch
We just open-sourced Lume - a tool we built after hitting walls with existing virtualization options on Apple Silicon. No GUI, no complex stacks - just a single binary that lets you spin up macOS or Linux VMs via CLI or API. Why we built Lume: - Run native macOS VMs in 1 command, using Apple Virtualization.Framework…
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Lume 0.2 – Build and Run macOS VMs with unattended setupJan 2026 · cua.ai · ▲154Hey HN, Lume is an open-source CLI for running macOS and Linux VMs on Apple Silicon. Since launch (https://news.ycombinator.com/item?id=42908061), we've been using it to run AI agents in isolated macOS environments. We needed VMs that could set themselves up, so we built that. Here's what's new in 0.2: *Unattended Setup* – Go from IPSW to a fully configured VM without touching the keyboard. We built a VNC + OCR system that clicks through macOS Setup Assistant automatically. No more manual setup before pushing to a registry: lume create my-vm --os macos --ipsw latest…
Lumier – Run macOS VMs in a Docker2025 · github.com · ▲159Hey HN, we're excited to share Lumier (https://github.com/trycua/cua/tree/main/libs/lumier), an open-source tool for running macOS and Linux virtual machines in Docker containers on Apple Silicon Macs. When building virtualized environments for AI agents, we needed a reproducible way to package and distribute macOS VMs. Inspired by projects like dockur/windows (https://github.com/dockur/windows) that pioneered running Windows in Docker, we wanted to create something similar but optimized for Apple Silicon. The existing…
OSS Python Framework for Running macOS and Linux VMs on Apple Silicon2025 · github.com · ▲5Building on the momentum of lume, we’re excited to share pylume, a new Python library that makes it easier to manage macOS and Linux virtual machines (VMs) on Apple Silicon directly from your Python code. pylume extends lume's command-line functionality to Python, giving developers the ability to integrate VM management into their Python scripts or applications. Why pylume? While lume makes managing VMs via the command line simple, pylume brings those features to Python, allowing developers to control VMs directly from their code. Here’s why pylume might be useful: • Native Python API:…
QEMU front end for M1 and Intel Macs2021 · mac.getutm.app · ▲418Securely run operating systems on your Mac
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Ollama – Run LLMs on your Mac2023 · github.com · ▲284Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…
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