pip install and a talking-head run_demo.py flow. That is not the 2026 product from tinyhumansai/openhuman. The real stack is a desktop agent plus Memory Tree built in Rust. This guide delivers four outcomes: install via signed native packages; sign in and run your first Memory Tree query; separate local data from hosted OAuth; and size RAM for large mailboxes plus optional local models. You get requirement tables, a six-step Runbook, a fix matrix, and host guidance.
What is OpenHuman in 2026, and how does it differ from OpenClaw or Hermes?
OpenHuman (GPL-3.0) is a local-first personal agent. One-click OAuth connects 100+ apps; email and documents land in SQLite plus an Obsidian-compatible Markdown vault called Memory Tree. OpenClaw excels at channel gateways and ClawHub skills—see our dual-stack rental guide. Hermes is CLI-first with hermes gateway and evolving Skills. OpenHuman targets desktop onboarding and memory compression (vendor claims up to ~80% token savings; verify on your workload).
Not a Python avatar pipeline: Skip conda, checkpoints/*.pth, and CUDA-only blog templates unless you are building unrelated video tooling.
Release line: Early Beta around v0.56.x as of June 2026; pin versions in production.
Coexistence cost: Running OpenClaw Gateway and OpenHuman ingestion on one 16 GB box competes for RAM—split hosts when both are production.
Trust model: Memory stays on disk locally; sign-in, model routing, and some OAuth proxies still use hosted services by default.
OpenHuman system requirements: macOS, Windows, and Linux compared
| Item | Minimum | Recommended |
|---|---|---|
| OS | macOS 12+, Windows 10+, Ubuntu 20.04+ | macOS 14+ (Apple Silicon) or Ubuntu 24.04 LTS |
| RAM | 4 GB (vendor docs) | 16 GB+ for large Gmail/repos plus on-device models |
| Disk | ~2 GB app footprint | 50 GB+ SSD for growing indexes and vaults |
| GPU | Not required for hosted models | Apple Silicon or NVIDIA only if you route locally |
| Install channel | Integrity | When to use |
|---|---|---|
| Homebrew / apt / MSI | OS package signing chain | Production default |
| npm -g openhuman | SHA-256 on downloaded binary | Node 18+ developers |
| curl | bash | No separate script signature | Quick trials only |
OpenHuman step-by-step install: six-step Runbook across four paths
brew tap tinyhumansai/core brew install openhuman openhuman --version
Pick a channel: Homebrew on macOS; signed apt repo on Debian/Ubuntu amd64; MSI from GitHub Releases on Windows; or npm install -g openhuman.
Verify: Run openhuman --version or check About in the desktop app (target v0.53+).
Sign in: Use the “Sign in! Let's Cook” screen; Advanced panel sets a custom core RPC URL for self-hosted cores.
Connect sources: Complete onboarding Gmail or other integrations; data writes to local Memory Tree storage.
First Memory Tree query: Ask something verifiable against ingested mail (e.g., summarize a labeled thread) to confirm retrieval, not generic hallucination.
Upgrade policy: Use brew/apt for updates; keep previous MSI/dmg builds for rollback during Beta.
OpenHuman configuration: local models, performance, and error fixes
| Symptom | Likely cause | Fix |
|---|---|---|
| Login spinner | Network or hosted auth outage | Change network/proxy; set Advanced RPC if self-hosting |
| OAuth denied | Browser or admin policy | Retry with system browser; check Workspace restrictions |
| Slow ingest / full disk | Large mailbox sync | Scope mailboxes; reserve 50 GB+; use 16 GB RAM |
| Local model OOM | 7B+ on 4 GB RAM | Stay on hosted routing or upgrade host |
For Ollama on the same Mac as OpenHuman, see the M4 dual-agent guide. Uninstall via package manager, then delete Memory Tree and vault directories from app settings to free space.
After install: 24/7 ingestion and Mac Mini M4 host numbers
GitHub traction: About 29k stars on openhuman as of June 2026, still Early Beta.
Power: M4 idle ~4–6 W; sync plus small local model often 18–28 W—reasonable for a dedicated ingestion node.
Unified memory: 16 GB UMA reduces swap thrash on SQLite FTS compared with 4 GB x86 VPS tiers.
Laptop sleep pauses mailbox deltas; Windows desktops lack macOS-grade background ergonomics. If you need Memory Tree to grow continuously with optional local models, MESHLAUNCH Mac Mini M4 bare-metal rental is usually the better production host: same brew workflow over SSH, launchd-friendly uptime, migratable data dirs before offboarding. Start on the pricing page; ops boundaries live in the help center.
No. Install via Homebrew, apt, or MSI. Python avatar tutorials target a different class of projects.
Yes. Hosted routing works immediately. For Ollama on-device, rent an M4 node to stress-test 24h ingestion.
GPL-3.0 applies to the open codebase; distributing proprietary forks triggers copyleft duties. Read vendor ToS for hosted login and routing.