Antigravity 2.0 ships as two front-ends onto the same agent engine, so the real question is not which is better but which matches the way you actually work. Choosing between Antigravity Desktop and the Antigravity CLI comes down to one fork: do you want to watch and steer agents in a visual app, or drive them headless inside scripts and pipelines? Both share the same runtime, so capability is not the deciding factor. Workflow is.

Quick Answer

Pick the Desktop app if your work is interactive: reviewing diffs, approving changes, and orchestrating several agents at once with full visibility. Pick the Go-based CLI if your work is scripted or headless: CI pipelines, automated refactors, and terminal-native developers who never leave their editor. They share preferences, permissions, and even active sessions, so most teams end up running both.

They Share One Engine

The two interfaces sit on the same agent harness, which is the most important thing to understand before choosing. Improvements to the core agents land in both at the same time, so you are not trading away intelligence by picking one over the other. The CLI is built in Go rather than the Node stack the older Gemini CLI used, which gives it snappier startup and a lighter memory footprint. Sessions sync bidirectionally too, meaning you can kick off a task in the terminal and pick it up in the Desktop app, or the reverse. That shared foundation is why the decision is about ergonomics, not power. If you are building out a machine to run agentic tooling locally, the AI PC range at Evetech covers the kind of memory and CPU headroom that multi-agent orchestration leans on.

When Desktop Is the Right Call

The Desktop app is the visual way to work. You get real-time view of what each agent is doing, can approve or reject individual changes, and keep tight control over the codebase. The centrepiece is multi-agent orchestration: set several agents on a problem at once, design custom subagent workflows, and schedule tasks to run in the background. Choose Desktop when:

  1. You want to see and approve changes before they touch your repo.
  2. You are running several agents in parallel and need to track them at a glance.
  3. You are building or debugging custom subagent workflows where visibility matters.
  4. You prefer a guided, click-to-confirm rhythm over typing commands.

When the CLI Is the Right Call

The CLI gives the same agent capabilities through the terminal, aimed at developers who do not want to leave their existing setup. It is the headless and automation choice. Reach for the CLI when:

  1. You are wiring agents into CI or a build pipeline where there is no screen to click.
  2. You want to script repeatable, repository-wide refactors that run unattended.
  3. You live in tmux, vim, or an SSH session and a GUI would only get in the way.
  4. You need the lower memory footprint and faster cold start on a constrained box or remote server.

Running Both Together

Because sessions and settings sync, the strongest setup for most people is not either-or. Use the CLI to launch long async jobs from the terminal, then open the Desktop app to inspect the diffs and approve the result. Or prototype a workflow visually, then commit it to a script the CLI runs on a schedule. The shared permission model means you configure trust once and it applies everywhere. A capable workstation makes this smoother, and the current best-selling desktop PCs give you a sense of the specs that handle parallel agents without stalling.

Frequently Asked Questions

Do Desktop and the CLI have different agent capabilities?

No. They run on the same agent harness, so core abilities and future improvements are identical across both. The difference is the interface and how you interact with the agents.

Why is the CLI built in Go?

Go gives the CLI faster startup and a smaller memory footprint than the Node-based Gemini CLI it replaces. That matters most on remote servers, CI runners, and lightweight machines where you want a lean process.

Can I move a session between the two?

Yes. Preferences, permissions, and active sessions sync bidirectionally, so you can start a task in the terminal and continue it in the Desktop app or vice versa.

Which should a beginner start with?

Desktop, in most cases. The visual approval flow makes it easier to learn what the agents are doing and to catch mistakes before they reach your code. Move to the CLI once you want automation.

Do I need a powerful PC to run either?

Not strictly, but multi-agent orchestration and large local workloads benefit from more RAM and a stronger CPU. A modern machine with generous memory keeps parallel agents and your editor responsive at the same time.

Setting up a workstation to run agentic coding tools properly? Browse the AI PC range at Evetech for systems with the memory and compute headroom that multi-agent workflows need.