nowfound

Commerce · August 14, 2026

Lumabri – Run Moe Models on a P2P Swarm with Colibri

A while ago I started working on Colibrì to see if it was possible to run huge LLMs on a normal computer. The project grew far beyond what I expected, thanks in large part to the HackerNews community. That led me to a new question: What if we stopped thinking about one computer? This is the idea behind Lumabri. Instead of requiring a single machine to store and run an entire huge model, Lumabri treats a network of normal computers as a shared pool of resources. One machine might provide disk space, another compute, another a different part of the model. If a required block or expert isn’t…

Lumabri – Run Moe Models on a P2P Swarm with Colibri launched on August 14, 2026 with 48 votes, #619 of 23,274 launches that month and more than 95% of that year's launches.

Visit github.com ↗Alternativestop 3% of August 2026

In plain words

Lumabri is a C-based engine that enables users to run large Mixture of Experts models across a peer-to-peer swarm network using the Colibri framework. It distributes model computation across multiple peers rather than requiring centralized infrastructure. The software is designed for developers and researchers who need to execute massive machine learning models efficiently using distributed resources.

written from the facts on this page · September 2026

From the sources

Run large AI models across your computers and servers. Powered by Colibri. Pure C. - JustVugg/lumabri

In the maker’s words, at launch

A while ago I started working on Colibrì to see if it was possible to run huge LLMs on a normal computer. The project grew far beyond what I expected, thanks in large part to the HackerNews community. That led me to a new question: What if we stopped thinking about one computer? This is the idea behind Lumabri.…

Does a similar job

all alternatives →
  • Getting GLM 5.2 running on my slow computerJul 2026 · github.com · ▲937

    A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…

  • Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series MacJul 2026 · github.com · ▲919

    Hi HN, I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal. I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…

  • Lume 0.2 – Build and Run macOS VMs with unattended setupJan 2026 · cua.ai · ▲154

    Hey 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…

  • Lume – OS lightweight CLI for MacOS and Linux VMs on Apple Silicon2025 · github.com · ▲309

    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…

  • Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhoneAug 2026 · github.com · ▲312

    Swiftlet is a Swift and Metal runtime that runs large Qwen Mixture-of-Experts models locally on Apple devices by streaming expert weights from storage, enabling 35B and 80B models to run with low RAM, including on iPhone. - leonickson1/Swiftlet

  • Ollama – Run LLMs on your Mac2023 · github.com · ▲284

    Hi 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…

Source: Show HN post ↗ · launch text quoted in part

Launched alongside, August 2026

the whole month →
  • TL

    Life & fun · Aug 2026 · louisabraham.github.io

  • Hey Noah▲656

    A proactive AI executive assistant for founders

    AI · Aug 2026 · heynoah.io

  • Hey HN, We recently built Clipto. It’s a tool that lets you search over terabytes of video, audio, and images on your computer, without relying on the cloud. Motivation: we probably all had this similar experience, we know a moment exists in a video or audio, but finding it takes hours scrubbing the timeline. You can send all the media to process in the cloud, but it’s slow, expensive and raises privacy concerns. So we decided to build our own on-device media search engine. How it works (high level): 1. We ingest video, audio, image; normalize formats via ffmpeg; run content analysis to…

    Work · Aug 2026 · clipto.com

  • Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…

    Life & fun · Aug 2026 · toneyalexander.github.io

  • AdAnt AI▲620

    Claude for viral, high-converting social ads

    AI · Aug 2026 · adant.ai

  • Astute▲606

    Automate your B2B brand going viral, with new media creators

    AI · Aug 2026 · company-app.joinastute.com