Google Agent
估算 Antigravity 2.0 长 Agent 任务、研究任务、内容生成和复杂构建对计划和 API 预算的压力。
Antigravity 的公开资料无法给出所有账号的精确私人限额，因此这页用任务类型、运行次数、复杂度和 token 假设做规划估算。
第一版中文页保留部分英文 API 字段、模型名和表单标签，方便和官方文档、价格表、开发工具配置项对应。计算结果只做预算和选型参考，最终价格、限额和条款以官方后台或服务商当前公开说明为准。
Google's I/O 2026 developer highlights describe Antigravity 2.0 as a standalone desktop application for orchestrating multiple agents in parallel, plus a CLI, SDK, managed agents, Google AI Studio export, Android support, Firebase integration, and Enterprise Agent Platform support.
Agentic coding tools do not behave like a single chat. One request can trigger planning, shell commands, web access, file edits, retries, and context compaction. A stalled loop can quietly burn tokens and plan quota.
Google's Antigravity Agent documentation says one API call provisions or reuses a Linux sandbox and starts a tool-use loop. The agent plans, acts, observes results, and repeats until the task is done. The same page says the agent is powered by Gemini 3.5 Flash, supports code execution, file management, Google Search, URL context, and automatic context compaction around 135k tokens.
The calculator uses the cost bands from Google's Antigravity Agent documentation as a sanity check and combines them with Gemini 3.5 Flash token pricing. Google lists typical examples such as research and information synthesis at about $0.30-$1.00, document generation at about $0.30-$1.30, process design at about $0.25-$0.80, and data analysis at about $0.70-$3.25. The docs also warn that complex workflows can accumulate 3-5 million tokens in a single interaction with costs up to about $5.
| Task type | Google documented range | Common risk | Control lever |
|---|---|---|---|
| Research & synthesis | $0.30-$1.00 | Too many searches and long source pages. | Limit sources and ask for checkpoints. |
| Document/content generation | $0.30-$1.30 | Large drafts and repeated revisions. | Use outlines before full generation. |
| Process/system design | $0.25-$0.80 | Over-broad goals that never converge. | Set acceptance criteria up front. |
| Data processing & analysis | $0.70-$3.25 | Large files, repeated code execution, and retries. | Sample data first, then scale. |
Google's developer highlights state that Google AI Ultra starts at $100 per month and includes a 5x higher usage limit in Google Antigravity than Google AI Pro. They also mention a limited-time $100 bonus-credit offer for Antigravity that expires May 25, 2026. This calculator does not know your private account quota, so it models plan pressure relatively: AI Ultra is treated as 5x the AI Pro baseline.
That relative model is useful for a purchase decision even without private quota numbers. If the same workload looks comfortable on AI Ultra but constrained on AI Pro, the decision becomes a value question: do you run enough agent work each month to justify the price difference, or would you rather keep Pro and use Gemini API pay-as-you-go only for the largest jobs?
Do not judge Antigravity from one successful demo. Track a small set of repeated task types for a week: research briefs, code edits, data analysis, document generation, and end-to-end workflow attempts. For each run, record the prompt, task category, whether the agent finished without intervention, rough wall-clock time, visible artifacts created, and whether the output needed a human rewrite. The useful cost is not only the billable estimate; it is the cost per accepted result.
This matters because autonomous agents can fail in expensive ways. A loop that keeps reading the same files, retrying a broken command, or expanding the task scope may look active while producing little value. A tight prompt with acceptance criteria, file limits, and a stop condition usually beats a broad prompt that asks the agent to "handle everything." If your first ten runs show many abandoned attempts, reduce task scope before you upgrade plans or increase API budget.
For team usage, also separate experimental credits from production credits. Exploration is noisy and should be capped. Production workflows should have a known owner, a repeatable prompt, a rollback plan, and a reason to run in an agent instead of a simpler script or normal model call.
For coding work, also separate exploration from execution. Let the agent inspect the repo and propose a scoped plan first, then run implementation after you approve the scope. This gives you a natural stop point before a vague request turns into a long autonomous loop with many tool calls.
No. Google does not publish a simple public token bucket for every Antigravity plan. This page estimates plan pressure from task count and complexity, then points you to the official app and billing dashboard for exact usage.
A normal model call produces one answer. Antigravity runs an autonomous loop with tools, file operations, command output, context compaction, and follow-up actions. That can accumulate far more input and output tokens.
Only if you consistently hit Pro limits or the 5x Antigravity limit plus other Ultra features are worth the monthly cost. For occasional API agent jobs, pay-as-you-go with a budget cap may be cleaner.
AI Code Limits is independent and is not affiliated with Google, Gemini, Google Antigravity, or Google AI Studio.