GBrain vs OpenComputer: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of GBrain and OpenComputer — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

GBrain

Paid

A shared team brain that syncs memory, connected apps and scheduled skills to ChatGPT, Claude, Cursor and any AI your team uses.

Shared Team Chat: The whole team prompts in one shared chat where anyone can follow up and see how answers were worked out.
Plain-File Memory: Team knowledge lives as markdown notes in folders you can open, correct and copy, and every AI answers from the fix.
Connect Once Credentials: Connect Gmail, Calendar, Drive, Stripe and more once; AIs receive call results, never passwords.
Per-AI Permission Levels: Set each AI to Off, Read, Draft, Manage or Full per account, with every action on one record.
Scheduled Skills: One-click skills like Team Standup, Customer Comms Tracker and Inbox Cleanup run daily or once.
Multi-AI Sync: Sync the same memory to Claude, ChatGPT, Cursor, Claude Code, Codex and your terminal.
Tools Plan: A password manager for AI that puts your applications into every AI you use for individuals.

Team Standups: Summarize the team's work across GitHub, Gmail and Calendar and email it out each morning.
Customer Follow-Up: Track customers and prospects owed a reply and flag overdue ones daily.
Issue Triage: Turn customer bugs and requests from email and support chats into deduplicated tracker issues.
Meeting Prep: Build sourced briefs on candidates, guests or investors before you meet.
Inbox Cleanup: Archive mail you never read on a schedule.
Pricing Decisions: Combine call notes and billing data in a shared chat to evaluate a price change.

Digger

Freemium

Background agent cloud that runs TypeScript agents on hardware-isolated Linux microVMs, with secrets the agent never sees.

Agent as a TypeScript Function: Declare a model, tools and MCP servers inside one exported function and deploy it live with `opencomputer deploy` — the platform owns the agent loop, sessions, streaming and versions.
Full Linux MicroVM Per Session: Each run gets a real machine with bash, a read-write filesystem, apt/npm/pip package installs and full network egress, isolated at the hardware level via KVM.
Durable Steerable Sessions: Runs stream to the client, accept mid-run steering, hibernate automatically when idle and resume exactly where they left off instead of restarting.
Origin-Bound Secret Injection: Secrets are defined per connection and injected only after a request leaves the sandbox, so the agent can act with a token it can never read or exfiltrate.
Checkpoint and Fork: Named snapshots work like git branches for VMs — fork a prepared machine to try five approaches in parallel, or restore one at any time.
Scheduled Autonomous Runs: A `defineSchedule` cron entry keeps a deployed agent running on its own, with sessions, streaming, MCP and Slack delivery handled by the platform.
Model-Agnostic Passthrough: The model is just a string that can change per request; token usage is passed through at raw API rates with no markup, or drops to zero with your own key or subscription.
Bare Sandboxes API: `Sandbox.create()` exposes the same microVMs directly — checkpoint, fork and live resize — for teams that want to bring their own harness and own the loop.

Codebase Hygiene Bots: Deploy an agent that finds stale feature flags still referenced in code and opens a cleanup pull request for each one on a weekday schedule.
Background Coding Agents: Hand off long refactors or migrations to an agent that clones the repo, runs the test suite in a real shell and works while you sleep.
Media and Data Pipelines: Run agents that need heavyweight binaries such as ffmpeg or headless Chromium, which serverless function runtimes cannot host.
Parallel Approach Exploration: Checkpoint a machine once the environment is prepared, then fork it to evaluate several agent strategies from an identical starting state.
Safe Third-Party API Automation: Let an agent operate on GitHub, Slack or an internal API through origin-bound credentials it is structurally unable to read or redirect.
Custom Agent Harness Hosting: Use the bare sandbox API as compute for an in-house agent framework, keeping your own loop while outsourcing VM lifecycle and scaling.