Google Antigravity Settings for Faster, Safer AI Coding

The top pick for most developers is the Balanced preset with Copilot-style suggestions enabled and a strict 2-second suggestion delay. It gives you fast, relevant completions without the distraction of constant pop-ups, and it keeps the AI from auto-accepting anything you haven’t reviewed.

What to Look For

When tuning Google Antigravity (or any AI coding assistant) for speed and safety, focus on these five criteria:

• Latency vs. Accuracy: Faster models (like a smaller local model) respond quicker but may hallucinate more. Slower models (larger, cloud-based) are more accurate but break your flow.
• Autocomplete aggressiveness: How many characters does the AI need before it suggests? Too low (1-2 chars) = constant noise; too high (10+) = you type everything yourself.
• Auto-accept behavior: Does the tool insert code without asking? For safety, always require a keystroke (Tab or Enter) to accept.
• Context window: How much of your current file and open tabs does the AI see? More context = better relevance, but slower and more token cost.
• Safety filters: Does the tool block insecure patterns (e.g., SQL injection, hardcoded secrets)? A good setting will flag or refuse to generate known dangerous code.

Option 1: Balanced Preset (Default)

Strengths: This is the default for a reason. It uses a medium-sized model (like Gemini 1.5 Flash or similar) that responds in under 300ms, suggests after 3-4 characters, and shows one or two lines of completion. It also includes basic security checks that flag obvious vulnerabilities.

Trade-offs: Not the fastest, not the smartest. For complex refactoring, it may suggest generic code that needs manual edits.

Best for: Most daily coding tasks—writing boilerplate, fixing syntax, and simple functions. It’s the safest starting point.

Option 2: Speed-First (Low Latency)

Strengths: Cuts suggestion delay to 0ms, uses a distilled model (like Gemma 2 2B) that runs locally, and only suggests after 2 characters. This feels instant—no flicker, no waiting.

Trade-offs: Accuracy drops noticeably. You’ll get more wrong completions, especially for complex logic. Safety filters are reduced to bare minimum (only blocks hardcoded secrets).

Best for: Rapid prototyping, writing repetitive code (e.g., getters/setters), or when you’re on a slow network and need offline speed.

Option 3: Accuracy-First (High Context)

Strengths: Uses the largest available model (e.g., Gemini 1.5 Pro) with a 128k token context. It reads your entire project structure, all open tabs, and even recent git diffs. Suggestions are remarkably relevant and often multi-line. Safety filters are at maximum—it will refuse to generate known insecure patterns and warns you about potential bugs.

Trade-offs: Latency can exceed 1 second, which breaks flow. Costs more in API credits if you’re on a metered plan. It can also overwhelm with too many suggestions.

Best for: Complex architectural changes, working in unfamiliar codebases, or when you need the AI to understand a large legacy system before editing.

Option 4: Strict Safety Mode

Strengths: This isn’t a single preset but a combination: enable “Security Review” (which scans every suggestion for OWASP Top 10 patterns), set suggestion delay to 5 seconds (so you have time to think), and disable auto-accept entirely. It also blocks any code that looks like a hardcoded API key or password.

Trade-offs: You lose most of the speed benefit. The AI becomes more of a reviewer than a writer—it will often say “I can’t suggest that” and offer a safe alternative instead.

Best for: Security-sensitive projects (fintech, healthcare, auth systems) or when you’re working with regulated data and need to minimize AI-induced vulnerabilities.

Option 5: Custom Profile (Power User)

Strengths: Antigravity allows you to create a custom profile where you control every parameter: model choice, suggestion delay, context size, and even custom instructions (e.g., “always use type hints”, “never use global variables”). You can also set different profiles per project.

Trade-offs: Requires time to tune. You need to know your own workflow—what’s too slow, what’s too noisy. It’s easy to over-optimize and end up with a setup that works for one file type but not another.

Best for: Developers who switch between languages (e.g., Python for data, JavaScript for web) and want different behavior per context.

How to Choose

Start with your budget: if you’re on a free tier, stick with Balanced or Speed-First—they use cheaper models. If you pay per token, Accuracy-First can get expensive quickly; use it only for complex tasks and switch back for routine edits.

Next, consider your use case: if you’re writing greenfield code, Speed-First is fine. If you’re modifying legacy code, Accuracy-First will save you hours of debugging. For anything that touches user data or authentication, always enable Strict Safety Mode.

Finally, accept the trade-off: you can’t have both ultra-fast and ultra-safe. The best approach is to create two profiles—one for “exploration” (fast) and one for “production” (safe)—and switch manually.

Frequently Asked Questions

Does Google Antigravity have a “safe” mode that blocks vulnerabilities?

Yes, there’s a “Security Review” toggle in settings. When enabled, it runs a lightweight static analysis on every suggestion and refuses to generate known dangerous patterns (e.g., SQL concatenation). It’s not a substitute for a dedicated security scanner, but it helps.

Will faster settings cause more hallucinations?

Generally, yes. Smaller models and shorter context windows increase the chance of plausible-looking but wrong code. If you notice frequent errors, switch to a larger model or increase the suggestion delay to give yourself time to review.

Can I set different settings for different projects?

Yes, Antigravity supports per-project profiles. You can save a “Fast” profile for a side project and a “Safe” profile for your main work, then switch with one click.

What’s the ideal suggestion delay?

For most people, 1-2 seconds is the sweet spot. Less than 1 second feels frantic; more than 3 seconds makes you forget the AI is there. If you’re a fast typer, go with 0ms and rely on manual acceptance.

Does auto-accept ever cause problems?

Yes—auto-accept is the most common source of “AI wrote a bug” complaints. It’s best to disable it and always press Tab to accept. This adds a split second but prevents accidental insertion of wrong code.

How do I know which model is being used?

In the settings, under “Model”, you’ll see the current model name. If you’re on a paid plan, you can choose between Flash (fast) and Pro (accurate). The free tier usually uses a smaller model.

Bottom Line

For 90% of developers, the Balanced preset with a 2-second delay and manual accept is the right choice. It’s fast enough to feel helpful, smart enough to be useful, and safe enough to avoid catastrophic errors. If you’re on a tight budget or a slow machine, switch to Speed-First; if you’re working on critical systems, enable Strict Safety Mode. The key is to never let the AI write code you don’t understand—always review before accepting.

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