Commerce · alternatives · 2026
24 alternatives to 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 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… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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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.…
Jul 2026 · github.com · its alternatives →
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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…
Jul 2026 · github.com · its alternatives →
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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…
Jan 2026 · cua.ai · its alternatives →
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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…
2025 · github.com · its alternatives →
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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
Aug 2026 · github.com · its alternatives →
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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…
2023 · github.com · its alternatives →
- 7WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat · its alternatives →
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TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
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I built slotstream, a way to run Qwen3.8-Flash-Next 4-bit on a low-memory mac starting from 16GB, a 125B parameter model that would need 100GB+ memory/RAM, thanks to expert-offloading/ssd-streaming. Easy to install/update, and mac-native using MLX and Swift. It ships with auto-mode, which makes a good tradeoff between memory usage and speed. I'll be implementing and porting the MTP module for speculative decoding next Local models really are the future of computing!
Sep 2026 · github.com · its alternatives →
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LM Studio▲209Discover, download, and run local LLMs (incl. DeepSeek R1)
2025 · lmstudio.ai · its alternatives →
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Hi HN, I’m Joe. My friends Matthew, Jake and I are building Luminal (https://luminalai.com/), a GPU compiler for automatically generating fast GPU kernels for AI models. It uses search-based compilation to achieve high performance. We take high level model code, like you'd have in PyTorch, and generate very fast GPU code. We do that without using LLMs or AI - rather, we pose it as a search problem. Our compiler builds a search space, generates millions of possible kernels, and then searches through it to minimize runtime. You can try out a demo in `demos/matmul` on mac to…
2025 · github.com · its alternatives →
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Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
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Hey 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…
2025 · github.com · its alternatives →
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Hi HN! I'm Nicolas, co-founder of Lume, a seed-stage startup (https://www.lume.ai/). At Lume, we use AI to automatically transform your source data into any desired target schema in seconds, making onboarding client data or integrating with new systems take seconds rather than days or weeks. In other words, we use AI to automatically map data between any two data schemas, and output the transformed data to you. We are live with customers and are just beginning to open up our product to more prospects. Although we do not have a sandbox yet, here is a video walkthrough of how…
2023 · lume.ai · its alternatives →
- 16RL
Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…
2023 · lepton.ai · its alternatives →
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SelfHostLLM▲134A simple calculator that estimates how many concurrent requests your GPU can handle for a given LLM, with shareable results.
2025 · selfhostllm.org · its alternatives →
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Qwen3.6-35B-A3B▲124The open sparse MoE model for agentic coding
Apr 2026 · qwen.ai · its alternatives →
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Hi HN! BLAST is a high-performance serving engine for browser-augmented LLMs, designed to make deploying web-browsing AI easy, fast, and cost-manageable. The goal with BLAST is to ultimately achieve google search level latencies for tasks that currently require a lot of typing and clicking around inside a browser. We're starting off with automatic parallelism, prefix caching, budgeting (memory and LLM cost), and an OpenAI-Compatible API but have a ton of ideas in the pipe! Website & Docs: https://blastproject.org/ https://docs.blastproject.org/ MIT-Licensed…
2025 · github.com · its alternatives →
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I've built this to make it easy to host your own infra for lightweight VMs at large scale. Intended for exec of AI-generated code, for CICD runners, or for off-chain AI DApps. Mainly to avoid Docker-in-Docker dangers and mess. Super easy to use with CLI / Python SDK, friendly to AI engs who usually don't like to mess with VM orchestration and networking too much. Defense-in-depth philosophy. Would love to get feedback (and contributors: clear & exciting roadmap!), thx
2025 · github.com · its alternatives →
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Hey Hacker News, We're the maintainers of docker/model-runner and wanted to share some major updates we're excited about. Link: https://github.com/docker/model-runner We are rebooting the community: https://www.docker.com/blog/rebooting-model-runner-community... At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any…
2025 · github.com · its alternatives →
- 24
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
Also compare
- Getting GLM 5.2 running on my slow computer alternatives
- Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac alternatives
- Lume 0.2 – Build and Run macOS VMs with unattended setup alternatives
- Lume – OS lightweight CLI for MacOS and Linux VMs on Apple Silicon alternatives
- Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhone alternatives
- Ollama – Run LLMs on your Mac alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →