OpenHuman 2026 Complete Installation Guide: From Zero to Running in Minutes (v0.56.0)
Intimidated by AI tool setup? This guide walks developers and beginners alike through all three installation paths — macOS Homebrew, Linux apt, and Windows .msi — for OpenHuman v0.56.0, then covers Memory Tree initialization, Ollama local model integration, and 24/7 Mac cloud hosting. Follow along and you'll be running in under 30 minutes.
Table of Contents
- What Is OpenHuman? Core Differentiators
- Three Deployment Pain Points
- OpenHuman vs OpenClaw vs Hermes Agent
- System Requirements & Prerequisites
- Installation (Five Paths)
- First Launch & Memory Tree Configuration
- Local Model Integration (Ollama + Apple Silicon)
- 24/7 Mac Cloud Deployment
- Real-World Use Cases
- FAQ
- Uninstall & Cleanup
1. What Is OpenHuman?
OpenHuman, built by tinyhumans.ai, is an open-source personal AI superintelligence for the desktop — "private, simple, and extremely powerful." Its standout characteristics:
- Memory Tree + Obsidian vault: Cross-session, cross-week memory that accumulates into a personal knowledge graph synced with your Obsidian .md files
- Screen awareness & desktop presence: A desktop mascot that sees your screen, reacts to what's happening, and can join Google Meets as a real participant
- 118+ OAuth integrations: Gmail, GitHub, Notion, Slack and more — no custom API wiring required
- TokenJuice cost routing: Automatically routes simple queries to cheaper models and complex tasks to powerful ones, minimizing API spend
- GNU GPL3 open source: Full source available; supports a custom core RPC URL for self-hosted backends
As of June 2026, OpenHuman v0.56.0 (released 2026-05-27) has surpassed 29,000 GitHub stars, making it one of the fastest-growing desktop AI assistant projects of the past quarter.
2. Three Deployment Pain Points Explained
- Complex environment setup: Most AI tools demand Python virtual environments, CUDA drivers, or Docker daemons. OpenHuman ships via system package managers — one command, no Python or GPU driver required.
- Privacy and data sovereignty concerns: Cloud AI subscriptions send conversation data to third-party servers. OpenHuman keeps your Memory Tree database, Markdown vault, and workspace config entirely on your machine.
- Laptop sleep kills background tasks: Closing the lid or hibernating ends Memory Tree sync, OAuth polling, and scheduled automations. Truly 24/7 AI operation needs a always-on node — which is exactly what Mac cloud hosting provides.
3. OpenHuman vs Competing Tools
| Dimension | OpenHuman v0.56.0 | OpenClaw | Hermes Agent |
|---|---|---|---|
| License | GNU GPL3 ✅ | MIT ✅ | MIT ✅ |
| Install difficulty | Homebrew / .msi, minutes ✅ | Terminal-first, needs Node ⚠️ | Terminal-first, needs Node ⚠️ |
| Memory system | Memory Tree + Obsidian vault 🚀 | MEMORY.md file ⚠️ | Skill Documents self-learning ✅ |
| External integrations | 118+ via OAuth 🚀 | MCP stdio tools ⚠️ | Telegram Gateway ✅ |
| Local model support | Ollama provider ✅ | Ollama provider ✅ | BYO models ⚠️ |
| Cost model | Subscription + TokenJuice routing ✅ | BYO API key ⚠️ | BYO API key ⚠️ |
| Screen awareness / avatar | ✅ Native | ❌ None | ❌ None |
4. System Requirements & Prerequisites
4.1 Minimum vs Recommended
| Item | Minimum | Recommended |
|---|---|---|
| OS | macOS 12+, Ubuntu 20.04+, Windows 10 | macOS 14+ / Ubuntu 22.04 / Windows 11 |
| RAM | 4 GB | 16 GB+ (local models / large mailbox ingestion) |
| Storage | 2 GB free | 10 GB+ (including Ollama model weights) |
| GPU | Not required (cloud model routing) | Apple Silicon M-series (best local inference) |
| Network | Required for first login | Stable broadband for model routing & OAuth |
4.2 Prerequisites by Platform
- macOS: Homebrew (verify with
brew --version); Ollama for local models - Linux (Debian/Ubuntu): gnupg2, curl, ca-certificates; apt 18.04+ with signed-by support
- Windows: No prerequisites — download the signed .msi and run it
5. Installation (Five Paths)
5.1 macOS — Homebrew (Recommended)
Homebrew handles signature verification and PATH setup automatically. After installation, run openhuman from terminal or launch from your Applications folder.
5.2 macOS — .dmg Manual Install
- Download the latest
.dmgfrom tinyhumans.ai/openhuman or GitHub Releases - Mount the .dmg, drag OpenHuman.app to Applications
- First launch: macOS may show "unidentified developer" — go to System Settings → Privacy & Security → Open Anyway
5.3 Linux — Signed apt Repository (Debian/Ubuntu)
5.4 Linux — AUR (Arch Linux)
5.5 Windows — Signed .msi Installer
- Go to github.com/tinyhumansai/openhuman/releases/latest
- Download
openhuman-setup-x64.msi - Run the installer and follow the wizard; find OpenHuman in the Start menu when done
6. First Launch & Memory Tree Configuration
6.1 Sign In
OpenHuman greets you with "Sign in! Let's Cook". Log in with Google, GitHub, or email. The Advanced panel lets you point the app at a custom core RPC URL for fully self-hosted operation — most users can skip this.
6.2 Memory Tree Initialization
After sign-in, the onboarding wizard initializes your Memory Tree:
- Choose vault directory: Point it at an existing Obsidian vault — OpenHuman reads and writes .md files directly
- Set ingestion scope: Select Gmail, GitHub Issues, Notion pages, etc. as memory sources
- Configure privacy levels: Decide which content may be sent to cloud models vs processed locally only
Default Memory Tree database paths:
6.3 Enabling OAuth Integrations
In Settings → Integrations, click any service icon to complete OAuth. Start with: Gmail, GitHub, Google Calendar, and Slack/Discord for maximum immediate value.
7. Local Model Integration (Ollama + Apple Silicon)
For zero-cost local inference on Apple Silicon, install Ollama alongside OpenHuman:
Then in OpenHuman Settings → Model Routing → Local AI:
- Set Provider to Ollama
- Enter endpoint
http://localhost:11434 - Select the downloaded model name (e.g.,
llama3.1:8b) - Configure TokenJuice: route everyday tasks to local model, fall back to cloud for complex reasoning
8. 24/7 Mac Cloud Deployment
Local machines have a fundamental flaw: laptop sleep, PC hibernation, or power loss interrupts OpenHuman's background tasks, Memory Tree sync, and OAuth polling. In production AI assistant scenarios, this leads to real problems:
- Task interruption: Google Meet attendance, long email processing jobs, and cron automations all die on sleep
- Memory Tree gaps: Events during offline windows (new emails, PR comments) never get ingested, leaving memory holes
- Remote maintenance difficulty: Keeping a local Mac awake while traveling is error-prone and unreliable
A VPSMAC M4 Mac cloud node solves all three: always online, native macOS environment fully compatible with OpenHuman, SSH accessible at any time. For teams using OpenHuman for production AI automation — email triage, meeting assistance, code review bots — renting a VPSMAC Mac node is typically more flexible and lower-maintenance than buying physical hardware.
Additional advantages of running OpenHuman on VPSMAC:
- Apple Silicon M4 native acceleration — Ollama local inference without GPU configuration hassle
- Data center network stability ensures reliable OAuth callbacks and Gmail webhook delivery
- On-demand memory scaling (16 GB → 32 GB → 64 GB) as your Memory Tree grows
9. Real-World Use Cases
Case 1: 24/7 Email Batch Processing
With Gmail connected, configure OpenHuman to scan your inbox hourly, draft replies to high-priority messages, and summarize threads into Memory Tree. On a Mac cloud node, this runs continuously even when your laptop is off.
Case 2: AI Participant in Google Meet
OpenHuman's desktop avatar joins Google Meet as a real participant, captures discussion points in real time, answers technical questions during the call, and automatically writes meeting notes into Memory Tree for future reference.
Case 3: Automated PR Code Review Bot
Connect GitHub integration and configure OpenHuman to pull diffs on new PRs, apply code standards from Memory Tree, generate draft review comments, and notify the responsible developer via Slack — all without manual triggering.
10. FAQ
Q1: Can I run OpenHuman without a GPU?
Yes. OpenHuman defaults to cloud model routing via TokenJuice (Claude, GPT, etc.) — no GPU required. For local inference, pair with Ollama on Apple Silicon for excellent results without a discrete GPU.
Q2: Does OpenHuman support Apple M-series chips?
Fully. The macOS build is natively optimized for Apple Silicon. M4's unified memory architecture lets you run 14B-parameter Ollama models alongside OpenHuman with low latency and excellent efficiency.
Q3: Where is my data stored?
Memory Tree database, Markdown vault, workspace config, and local runtime state all live on your machine. Only model routing requests and login sessions use hosted services. Power users can configure a custom core RPC URL for complete self-hosting.
Q4: How do I update OpenHuman?
Q5: Can I back up my Memory Tree data?
Yes. The Memory Tree DB is a standard SQLite file — copy it for backup. The Markdown vault portion integrates naturally with Git or Obsidian Sync for version control.
Q6: Is commercial use allowed?
OpenHuman is licensed under GNU GPL3, which requires modified versions to be open-sourced (copyleft). tinyhumans.ai offers commercial licensing — enterprise users should contact them for a commercial license.