Antigravity vs Gemini CLI: which costs less?

Part of the reduce AI coding agent token usage pillar. Both tools here are Google's.

Should I use Antigravity or Gemini CLI?

Gemini CLI if your work is many small, predictable requests; Antigravity if it is fewer, heavier agent tasks. They meter opposite things, and picking the wrong one means the meter you chose punishes exactly the workload you have. That is the whole comparison in one line, and it is unusual. Most tool pairs differ on features. These two differ on what a unit of consumption is, which changes the answer depending on how you work rather than on which is better.

How does Gemini CLI's quota work?

It counts requests. 60 per minute and 1,000 per day on the free tier with a personal Google account. That is a clean, predictable meter. A request is a request whether it took the model two seconds or two minutes, and 1,000 a day is generous for interactive work. You get Gemini 3 models with a 1M token context window, no API key management if you sign in with a Google account, and Google Search grounding built in. The predictability is the feature. You can plan against 1,000 requests in a way you cannot plan against a quota that varies with task difficulty. If you want higher limits, an API key from AI Studio or a Google Cloud billing account moves you to usage-based billing.

How does Antigravity's quota work?

It measures how much work the agent did, and that is Google's own description, not an inference. Per Antigravity's plans documentation: "the rate limits are correlated with the amount of work done by the agent, which can differ from prompt to prompt. Thus, you may get many more prompts if your tasks are more straightforward and the agent can complete the work quickly, and the opposite is also true." Read that carefully, because it inverts the usual mental model. There is no fixed number of prompts. A simple question costs little; a task where the agent reads twenty files, runs the tests twice and rewrites a module costs a lot. Two people on the same plan can get very different numbers of prompts out of the same week. The refresh schedule differs by plan: All plans get Gemini 3.1 Pro and Gemini 3.8 Flash as the core agent model, unlimited Tab completions, and every product feature including Scheduled Tasks and the CLI.

What happens when you run out?

On Gemini CLI, you wait or you move to billing. On Antigravity, you can buy through it — if you turned that on. Antigravity users on AI Pro or Ultra can spend purchased AI credits for overage above the baseline quota, consumed at standard Gemini Enterprise Agent Platform pricing. That behaviour is governed by an "AI Credit Overages" user setting, which is worth finding before you need it rather than during an outage. The distinction matters for how each tool fails. Gemini CLI's request cap is a wall: you stop. Antigravity's is a wall that can become a slope, which is better when a deadline does not care about your quota and worse if you have not decided in advance what you are willing to spend.

Which one does a heavy task punish?

Antigravity, by design — and that is not a flaw, it is the meter being honest. A work-correlated quota charges you for what the agent actually did. Reading whole files, re-running a test suite, exploring a repository it does not need to explore: all of that is work, and all of it is now visible in your quota rather than hidden behind a request count. Which means the levers that reduce token usage are the same levers that stretch an Antigravity quota. On Gemini CLI, a wasteful agent still costs one request; on Antigravity, waste is metered. If you are moving from one to the other, expect the same habits to produce different bills. Google's own caveat is worth repeating: the baseline limits are set "primarily determined to the degree we have capacity" and "exist to prevent abuse", and are explicitly "subject to modification". Neither meter is a contract.

How to apply this today

1. Count your requests for a week on Gemini CLI. If you are nowhere near 1,000 a day, the free tier is not your constraint and the comparison is about features, not cost.
2. If your work is heavy agent tasks, expect Antigravity's quota to move with difficulty, not with prompt count. Budget in tasks completed, not prompts sent.
3. Find the AI Credit Overages setting before you need it. Decide the behaviour in advance.
4. On Antigravity, treat token discipline as quota discipline. Fewer whole-file reads and less unfiltered command output mean literally more prompts per week.
5. Check which refresh you are on. Five-hourly on Pro and Ultra, weekly otherwise — that changes how you pace a day.

What goes wrong (anti-patterns)

Comparing them on prompt counts. One publishes a number of requests, the other explicitly says the number of prompts varies with task difficulty. Those figures are not the same unit and lining them up produces a meaningless ratio. Assuming a work-metered quota is worse. It charges for what the agent did, which also means efficiency is rewarded directly. On a request meter, being wasteful is free until it is not. Planning around limits Google calls provisional. They are described as capacity-driven and subject to modification. Build a habit, not a spreadsheet. Migrating and blaming the tool for a bigger bill. Moving from a request meter to a work meter surfaces waste that was always there. That is information, not a regression — reduce Google Antigravity token usage covers what to do about it.

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See also:

• How to reduce Google Antigravity token usage — the quota, the /usage panel, and the levers
• Reduce AI coding agent token usage — the pillar
• How to measure agent token usage — the number to establish before switching tools