OpenGraviton

OpenGraviton is an open-source engine that runs 500B+ parameter LLMs locally on consumer hardware like a Mac Mini. It compresses and streams models to fit in limited memory, democratizing access to powerful AI.

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At a glance

Pricing

Open Source · Free

Free tier

Yes

API

Yes

Skill level

Technical

About

What is OpenGraviton?

OpenGraviton is an open-source AI inference engine designed to run large language models (LLMs) with over 500 billion parameters directly on consumer hardware, such as a Mac Mini. It aims to break free from cloud monopolies by enabling local AI execution, eliminating the need for cloud subscriptions, API rate limits, or data harvesting. The engine achieves this by compressing models up to 10x (down to 1.58-bit) and streaming them layer-by-layer, allowing even models too large for RAM to run from an SSD. It features fast generation through speculative decoding and dynamic sparsity, and includes a headless API server for AI agents on low-budget machines, supporting Apple Silicon, NVIDIA GPU, or CPU. A chat UI is also included for immediate use.

Best used for

Ideal for developers and data scientists who need to run powerful AI models locally, develop AI agents on low-budget hardware, and experiment with large language models without cloud dependencies. Especially valuable for those seeking to break free from cloud monopolies and ensure data privacy.

Common actions

run LLMs locally

develop AI agents

compress AI models

democratize AI

Capabilities

Key features

Run 500B+ LLMs locally
Compress models up to 10x
Stream models layer-by-layer
Headless API server
Fast generation
Chat UI included
Supports Apple Silicon/NVIDIA/CPU

Target Audience

developerdata scientiststartup founderstudent

Integrations

Not yet documented

Pricing & Plans

Open Source · Free

Open Source

FAQs

What kind of hardware is required to run OpenGraviton?

OpenGraviton is designed to run on consumer hardware, including Mac Minis and laptops. It supports Apple Silicon, NVIDIA GPUs, and CPUs. While it can run 72B models on a Mac with 64 GB RAM, its streaming and compression features allow it to handle even larger models by loading them from your SSD layer-by-layer.

How does OpenGraviton enable running large models on limited memory?

OpenGraviton employs two key techniques: model compression and layer-by-layer streaming. It compresses AI models from 16-bit down to 4-bit or even 1.58-bit, making them 4 to 10 times smaller. Additionally, it streams models one layer at a time from your SSD, compressing each layer instantly, so the entire model never needs to fit into RAM simultaneously.

Can OpenGraviton be used for AI agents or headless applications?

Yes, OpenGraviton includes a headless API server with zero UI dependencies. This allows AI agents on low-budget machines to load and utilize 70B+ models through a simple REST API. This feature is ideal for integrating powerful AI capabilities into applications without requiring a GPU cluster or cloud infrastructure.

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