Google AI Studio — Gemini-powered AI Web IDE + app builder
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Google AI Studio — Gemini-powered AI Web IDE + app builder
Google AI Studio (aistudio.google.com) is the in-browser home for the Gemini family. It started as a prompt playground, but since 2024 it has grown into a notebook + app builder + auto-deploy environment — squarely in the same AI Web IDE category as Replit.
1. Four faces in one tab
| Face | What it is |
|---|---|
| Prompt playground | Single-shot Gemini API tests. Tweak system instruction, temperature, safety filters. |
| API key issuance | Free key from one Google account. Separate from Vertex AI (no org/billing required). |
| AI notebook (formerly Studio Library) | Auto-generates code for RAG, function calling, multi-turn chat. |
| Build (NL → app) | Prompt → Vite/Next app → auto-deploy to Cloud Run. |
notes/ai/04-gemini-api covers the API side. This note focuses on the AI Web IDE and app builder faces.
2. Where AI Studio fits
| Year | Event |
|---|---|
| 2023-12 | MakerSuite launches alongside Gemini Pro 1.0. |
| 2024-02 | Rebranded to Google AI Studio. |
| 2024-05 | Gemini 1.5 Pro/Flash · 1M-token context, free key. |
| 2024-12 | Multimodal Live API (image/audio/video). |
| 2025+ | Build mode — generate and deploy apps from prompts. |
| 2025+ | Stitch (UI design) · NotebookLM hooks. |
Core value:
- All Gemini 1.5/2.0 models + 1M-token context, free (within rate limits).
- Auto-generates code (Python · Node.js · cURL · Swift · Kotlin · Dart).
- Auto-deploy (Cloud Run · Firebase Hosting).
- Tight Workspace · Drive · Maps integration.
3. AI Studio vs Vertex AI
Same Gemini models, two entry points:
| Aspect | AI Studio | Vertex AI |
|---|---|---|
| Entry | Single Google account | GCP org · project · billing |
| URL | aistudio.google.com |
GCP Console → Vertex AI |
| Billing | Free (rate limit) + paid key | GCP usage |
| Data policy | Free key may train models (opt-out available) | Enterprise — no training (default) |
| SDK | @google/genai |
@google-cloud/vertexai |
| Auth | API key | OAuth · service account |
| Deploy hooks | Cloud Run · Firebase | Vertex AI Endpoints |
| Sweet spot | learning, side projects, PoCs | production, compliance |
Common pattern: start with AI Studio key → graduate to Vertex AI. Same model IDs, so the migration is mostly an SDK swap.
4. Build mode — NL → app → deploy
aistudio.google.com/apps for Build mode.
"An app where I upload a photo and Gemini writes a description"
↓
1. Gemini picks the stack (Vite + React + Tailwind).
2. Generates file tree, installs deps automatically.
3. Auto-injects the Gemini API key as an env var.
4. Preview in the in-browser webview.
5. Click "Deploy to Cloud Run" → auto-deploys + URL.
What you get:
- Frontend — Vite/Next or static HTML.
- Backend — Cloud Run Functions (when needed) or direct client→Gemini calls.
- Auth — Firebase Auth (optional).
- DB — Firestore · Cloud SQL (optional).
GitHub auto-sync (Build can export to your repo). Best for learning · hackathons · PoCs.
5. AI notebook (Live API · function calling)
Use the GUI to try complex flows — RAG · tool use · multi-turn chat. Then click Get code to copy the equivalent Python/Node.js SDK code.
# Get code result (Python)
from google import genai
client = genai.Client(api_key="AIzaSy...")
response = client.models.generate_content(
model="gemini-2.0-flash-exp",
contents="Hello",
)
print(response.text)
Same flow for Node.js · Swift · Kotlin · Dart.
6. Free quota — actual limits
As of 2026-05 (subject to change):
| Model | RPM (per min) | TPM (per min) | RPD (per day) |
|---|---|---|---|
| Gemini 2.0 Flash Exp | 10 | 1M | 1,500 |
| Gemini 1.5 Pro | 2 | 32K | 50 |
| Gemini 1.5 Flash | 15 | 1M | 1,500 |
| Gemini 2.5 Pro / Flash | (varies) | (varies) | (varies) |
Free-key inputs may be used for model training (opt-out available). For sensitive data, prefer Vertex AI.
Switching to a paid key (Pay-as-you-go) → no training + larger quotas.
7. AI Studio vs Replit / Bolt.new / v0.dev
| Aspect | AI Studio Build | Replit Agent | Bolt.new | v0.dev |
|---|---|---|---|---|
| Model | Gemini only | Anthropic + opt | Anthropic | OpenAI · Anthropic |
| Backend | Cloud Run · Firebase | Reserved VM | partial (WebContainer) | ✗ |
| DB | Firestore · Cloud SQL | Replit DB · PG | ✗ | ✗ |
| Deploy | Cloud Run auto | Replit Reserved | Vercel / Netlify | Vercel |
| Free | Gemini quota | sleep + 1 Static | limited | ✓ |
| Strength | Google ecosystem · 1M-token context | learning · collab | quick SPA PoCs | UI components |
| Weakness | Google lock-in | costly when busy | thin backend | front-end only |
Pick by:
- Already on GCP + 1M-token context → AI Studio Build.
- Learning / pair programming + collab → Replit.
- Quick Vite/Next PoCs → Bolt.new.
- shadcn/ui components → v0.dev.
8. Good fit / poor fit
Fits:
- Gemini experiments / PoCs.
- Combining Workspace · Drive · Maps · YouTube APIs.
- RAG over very long documents (1M-token context shines).
- Auto-generated learning apps.
- Function calling · Live API trials.
Poor fits:
- Strict compliance worries about training-on-input — use Vertex AI.
- Tasks where Anthropic/OpenAI models clearly win (varies by task).
- Above-quota traffic.
- Avoiding Google ecosystem lock-in.
9. Data / training policy (important)
AI Studio free key:
- Inputs/outputs may be used for model training (default on).
- Privacy controls let you opt out.
- 30-day retention (for debugging).
AI Studio paid key (Pay-as-you-go):
- No training (default).
- Short retention (24–48h).
Vertex AI:
- No training (default).
- Separate retention policy.
Use a paid key or Vertex AI for any work / sensitive data.
10. Further reading
- Google AI Studio
- AI Studio Build
- Gemini API note — the API side
- Replit — another AI Web IDE
- AI coding IDE comparison — desktop side
- AI Web IDE roundup — browser side