Google Jules vs Antigravity (2026): What's the Difference?

How Jules and Antigravity differ

Google has two coding agents, and the simplest way to tell them apart is where the work happens. Jules works asynchronously in the cloud on your GitHub repos, while Antigravity runs agents on your own machine as you work.

Jules takes a task, a repository, and a branch, then clones the repo into a cloud VM, proposes a plan for your approval, makes the changes, and opens a pull request for you to review. Because the work happens off your machine, you can hand it bug fixes, tests, or dependency updates and come back to a diff. Beyond the web app, Google also offers Jules Tools, a command-line companion, and announced a public API in preview alongside it.

Antigravity is Google's agentic development platform, made up of an agent-first IDE, Antigravity 2.0 for managing several local agents in parallel, a terminal CLI, and a Python SDK for prototyping custom agents. It's built for keeping agents in the loop while you work, so you can run background subagents from the terminal, schedule recurring tasks, and use browser-in-the-loop agents for frontend work. It runs on macOS, Windows, and Linux.

Jules vs Antigravity pricing

Both have a free tier and both scale through Google AI Pro and Ultra subscriptions, but they meter usage differently.

Jules limits you by tasks. The free plan allows 15 tasks a day with 3 running at once on Gemini 2.5 Pro, while Google AI Pro raises that to 100 tasks and 15 concurrent, and Ultra to 300 tasks and 60 concurrent, with access to newer models starting with Gemini 3 Pro.

Antigravity's pricing uses weekly rate limits on the free individual plan, with higher limits and a shared AI credit pool on Pro and Ultra. For organizations, the Business plan through Google Cloud costs $30 per seat per month, or you can pay as you go with no seat fee.

Task limits make Jules easy to plan around when you're delegating chores, while Antigravity's rate limits matter more if agents are part of your editor all day.

Respan for the LLM apps you build with them

Jules and Antigravity help you write the code, but once the app you're building makes its own LLM calls, those calls need to be routed and monitored in production. Respan is the AI router with built-in observability and automated evals, so your app reaches 1,000+ models through one OpenAI-compatible endpoint.

Each request your app makes is traced with its cost, latency, and token usage, and that production traffic feeds the evals that catch quality regressions before users do. Fallback chains and spend controls live alongside those traces, so when a provider fails or costs jump, you can see which requests caused it.

If you're building an LLM app with either agent, Respan lets you route, observe, and evaluate every LLM call it makes, starting on the free tier. For the coding itself, Jules fits teams that want to hand off well-scoped tasks and review PRs, while Antigravity fits developers who want agents working inside their editor and terminal.