How to Use Gemini 3.0 Pro with Cursor (2026)

Gemini 3.0 Pro is Google's most capable AI model, offering excellent performance in coding, reasoning, and long-context understanding. While Cursor comes with built-in support for Claude and GPT models, you can also connect it to Gemini 3.0 Pro through Google's API -- and the best part is that Google AI Studio provides a generous free tier.

This guide walks you through every step of setting up Gemini 3.0 Pro in Cursor, from getting your API key to optimizing your configuration for the best coding experience.

Why Use Gemini 3.0 Pro in Cursor?

There are several compelling reasons to add Gemini 3.0 Pro to your Cursor setup:

Advantage	Details
Free tier	Google AI Studio provides 15 RPM and 1,500 requests/day for free
1M+ context window	Largest context window of any major model -- ideal for large codebases
Strong coding	Competitive with Claude and GPT on coding benchmarks
Fast inference	Google's infrastructure delivers low-latency responses
Multimodal	Can analyze images, diagrams, and screenshots alongside code

How Gemini 3.0 Pro Compares for Coding

Benchmark	Gemini 3.0 Pro	Claude Sonnet 4	GPT-5
HumanEval	93.1%	94.8%	95.2%
SWE-bench Verified	52.8%	58.3%	55.8%
LiveCodeBench	65.2%	71.2%	68.3%
MATH-500	92.1%	91.4%	92.7%
Context Window	1M+ tokens	200K tokens	256K tokens

Gemini 3.0 Pro is competitive on coding benchmarks and excels in scenarios requiring large context windows. Its free tier makes it an excellent complement to Cursor's built-in models.

Prerequisites

Before you start, make sure you have:

Cursor installed (download from cursor.com)
Google account (free Gmail account works)
Google AI Studio API key (we will create this in Step 1)

Step 1: Get a Google AI Studio API Key

Go to aistudio.google.com
Sign in with your Google account
Click "Get API key" in the left sidebar
Click "Create API key"
Select a Google Cloud project (or create a new one -- it is free)
Copy the generated API key

# Test your API key with a curl command
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.0-pro:generateContent?key=YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [{"text": "Write a hello world function in Python"}]
    }]
  }'

If you get a JSON response with generated code, your API key is working.

Google AI Studio Free Tier Limits

Limit	Free Tier
Requests per minute	15
Requests per day	1,500
Tokens per minute	1,000,000
Context window	1,048,576 tokens
Price	$0

For individual developers, 1,500 requests per day is generous enough for a full day of coding with Cursor.

Step 2: Configure Gemini in Cursor

There are two ways to add Gemini 3.0 Pro to Cursor: through the built-in model settings or through an OpenAI-compatible API endpoint.

Method A: Cursor's Built-in Google AI Integration

Cursor has added native support for Google AI models. This is the simplest setup:

Open Cursor
Go to Settings (gear icon) > Models
Scroll down to "Google AI" or "Gemini"
Enter your Google AI Studio API key
Select Gemini 3.0 Pro from the model dropdown
Click Save

You can now select Gemini 3.0 Pro from the model picker in any Cursor chat or Agent session.

Method B: OpenAI-Compatible API Endpoint

If Method A is not available in your Cursor version, you can use Google's OpenAI-compatible endpoint:

Open Cursor
Go to Settings > Models
Click "Add custom model" or "OpenAI API Key"
Configure the following:

API Key: YOUR_GOOGLE_AI_STUDIO_KEY
Base URL: https://generativelanguage.googleapis.com/v1beta/openai
Model name: gemini-3.0-pro

Save the configuration

Method C: Via OpenRouter (Multi-Model Access)

OpenRouter provides a unified API for multiple models. This method lets you access Gemini alongside Claude, GPT, and other models through a single API key:

Create an account at openrouter.ai
Add credits or use the free tier
Get your OpenRouter API key
In Cursor, go to Settings > Models
Add a custom model:

API Key: sk-or-your-openrouter-key
Base URL: https://openrouter.ai/api/v1
Model name: google/gemini-3.0-pro

Step 3: Set Gemini as Your Default Model

To use Gemini 3.0 Pro as your primary model in Cursor:

Open any Cursor chat panel (Cmd+L / Ctrl+L)
Click the model name at the top of the chat panel
Select Gemini 3.0 Pro from the dropdown
Cursor will remember your selection for future sessions

You can also set it as the default for specific features:

Feature	How to Set Model
Chat	Model picker in chat panel
Agent mode	Model picker in Agent panel
Cmd+K (inline edit)	Settings > Models > Default for inline edits
Cursor Tab	Settings > Models > Default for completions

Tip: Use Gemini 3.0 Pro for chat and agent tasks (where its large context window shines), and keep Cursor's default model for Cursor Tab autocomplete (which benefits from lower latency).

Step 4: Optimize Your Workflow

Use Gemini for Large Codebase Tasks

Gemini 3.0 Pro's 1M+ token context window makes it ideal for tasks involving large codebases:

# In Cursor Agent mode with Gemini 3.0 Pro:
"Analyze the entire src/ directory and create a dependency graph
showing which modules depend on each other. Identify any circular
dependencies and suggest how to resolve them."

With a 1M token context, Gemini can process hundreds of files in a single request -- something that requires careful chunking with Claude or GPT.

Use @-Mentions for Context

Cursor's @-mention feature works with any model, including Gemini:

# Reference specific files
@src/api/auth.ts @src/middleware/jwt.ts
"Why is the JWT validation failing for expired tokens?"

# Reference the entire codebase
@codebase
"Find all endpoints that don't have rate limiting and add it"

# Reference documentation
@docs
"Update the API docs to match the current endpoint signatures"

Configure Rules for Gemini

Create a .cursorrules file in your project root to give Gemini consistent instructions:

# .cursorrules
You are a senior full-stack developer working on a Next.js 15 application.

Tech stack:
- Next.js 15 with App Router
- TypeScript (strict mode)
- Tailwind CSS
- Prisma ORM with PostgreSQL
- tRPC for API layer

Conventions:
- Use server components by default, client components only when needed
- All API routes should have input validation with Zod
- Use TypeScript strict mode with no 'any' types
- Write tests for all business logic
- Use descriptive variable names, no abbreviations

Step 5: Compare Gemini with Other Models in Cursor

One of Cursor's strengths is multi-model support. You can easily switch between models to compare their output on the same task.

Practical Comparison Test

Try this prompt with each model to compare quality:

"Write a TypeScript function that:
1. Accepts a nested object of any depth
2. Flattens it into a single-level object with dot-notation keys
3. Handles arrays, null values, and circular references
4. Includes comprehensive type definitions
5. Has unit tests"

When to Use Each Model

Task	Best Model	Why
Large codebase analysis	Gemini 3.0 Pro	Largest context window
Complex refactoring	Claude Sonnet 4	Best coding benchmark scores
General coding	GPT-5	Strong all-around
Quick fixes	GPT-4o or Gemini Flash	Fastest response
Architecture decisions	Claude Opus 4	Best reasoning
Documentation writing	GPT-5	Best creative writing

Troubleshooting

"Model not found" Error

If Cursor cannot find the model, double-check:

# Correct model name for Google AI Studio
gemini-3.0-pro

# For OpenRouter
google/gemini-3.0-pro

Rate Limit Errors

If you hit the 15 RPM limit on Google AI Studio's free tier:

Slow down your request rate (wait a few seconds between prompts)
Use Cursor Tab with a different model to reduce Gemini API calls
Upgrade to Google AI Studio's paid tier ($0 for the first tier, pay-as-you-go after free limits)

Slow Responses

Gemini 3.0 Pro responses may be slower than Cursor's default models because requests route through Google's API rather than Cursor's optimized infrastructure. To mitigate:

Use Gemini 3.0 Flash for latency-sensitive tasks (autocomplete, quick edits)
Use Gemini 3.0 Pro for complex tasks where quality matters more than speed

API Key Not Working

# Verify your key works outside Cursor
curl "https://generativelanguage.googleapis.com/v1beta/models?key=YOUR_API_KEY"

# Expected: JSON list of available models
# If error: regenerate your key in Google AI Studio

Frequently Asked Questions

Is Gemini 3.0 Pro really free in Cursor? Yes, if you use a Google AI Studio API key. The free tier gives you 1,500 requests per day at no cost. You only pay if you exceed the free limits.

Is Gemini 3.0 Pro as good as Claude for coding? Claude Sonnet 4 and Opus 4 currently score higher on coding benchmarks like SWE-bench. However, Gemini 3.0 Pro is competitive and its 1M+ context window is a significant advantage for large codebases.

Can I use Gemini 3.0 Pro in Cursor's Agent mode? Yes. Once configured, Gemini 3.0 Pro works in chat, agent mode, and inline edits. Select it from the model picker in any Cursor panel.

Does this count against my Cursor Pro request limits? No. When you use your own API key (Google AI Studio, OpenRouter, etc.), requests are billed to your API account, not your Cursor subscription. This effectively gives you unlimited Cursor usage.

Can I use Gemini Flash for Cursor Tab? Yes. Set Gemini 3.0 Flash as the model for Cursor Tab (autocomplete) for fast, low-latency completions, and use Gemini 3.0 Pro for chat and agent tasks.

Wrapping Up

Adding Gemini 3.0 Pro to Cursor gives you access to Google's most capable model with a generous free tier. Its 1M+ token context window is particularly valuable for large codebase analysis, and the free 1,500 requests per day is enough for a full day of productive coding.

If you are building applications that need AI-generated media, try Hypereal AI free -- 35 credits, no credit card required. Hypereal's API for image generation, video creation, and text-to-speech integrates naturally into any Cursor development workflow.