2025 Complete Guide: Gemini 2.5 Computer Use Model - Revolutionary Breakthrough in AI Agent Interface Control

🎯 Key Takeaways (TL;DR)

• Breakthrough Technology: Google releases the first Gemini 2.5 Computer Use model specifically designed for interface control
• Outstanding Performance: Gemini 2.5 Computer Use outperforms competitors in multiple web and mobile control benchmarks with lower latency
• Practical Value: Gemini 2.5 Computer Use enables building agent applications for automated form filling, web navigation, UI testing, and more
• Security Assurance: Gemini 2.5 Computer Use features built-in multi-layer security mechanisms including user confirmation and real-time safety checks
• Immediately Available: Gemini 2.5 Computer Use preview version available through Gemini API on Google AI Studio and Vertex AI platforms

Table of Contents

1. What is Gemini 2.5 Computer Use Model
2. Core Working Principles
3. Performance and Benchmarks
4. Supported Action Types
5. Development Implementation Guide
6. Security Mechanisms and Best Practices
7. Real-world Use Cases
8. Pricing and Availability
9. Frequently Asked Questions

What is Gemini 2.5 Computer Use Model

Gemini 2.5 Computer Use is a specialized model built by Google based on Gemini 2.5 Pro's visual understanding and reasoning capabilities, designed specifically for controlling user interfaces. Unlike traditional software interaction through structured APIs, this model can interact directly with graphical user interfaces just like humans do.

Core Features

• Visual Understanding: Ability to "see" computer screens and understand interface elements
• Action Generation: Generates specific UI operation instructions (click, type, scroll, etc.)
• Multi-platform Support: Primarily optimized for web browsers while supporting mobile control
• Real-time Feedback: Adjusts subsequent behavior based on operation results

💡 Technical Breakthrough
This is the first large language model specifically optimized for interface control tasks, filling an important gap in AI-graphical interface interaction.

Core Working Principles

The Gemini 2.5 Computer Use model employs a cyclical interaction mechanism, with the entire process divided into four core steps:

1. Send Request to Model

• Add Computer Use tool to API request
• Provide user goal and current GUI screenshot
• Optionally exclude specific actions or add custom functions

2. Receive Model Response

• Model analyzes user request and screenshot
• Generates response containing function_call representing specific UI operations
• May include safety decisions requiring user confirmation

3. Execute Received Actions

• Client code parses and executes function_call
• Determines if user confirmation is needed based on safety decision
• Executes action in target environment (e.g., browser)

4. Capture New Environment State

• Capture new GUI screenshot after action execution
• Send result back to model as function_response
• Begin new cycle until task completion

⚠️ Important Notice
Must use the gemini-2.5-computer-use-preview-10-2025 model; other models do not support the Computer Use tool.

Performance and Benchmarks

Gemini 2.5 Computer Use demonstrates outstanding performance across multiple authoritative benchmarks:

Main Benchmark Results

Performance Characteristics

• Leading Accuracy: Surpasses existing solutions in web and mobile control tasks
• Lowest Latency: Provides industry-leading response speed
• Stable and Reliable: Maintains high success rate in complex interface scenarios

✅ Benchmark Validation
Test results come from self-reported data, Browserbase evaluations, and Google internal testing. Detailed information available in official evaluation documentation.

Supported Action Types

The Gemini 2.5 Computer Use model supports a rich set of UI operation types, covering all aspects of daily interface interaction:

Basic Operations

Advanced Operations

Special Functions

• Wait Mechanism: wait_5_seconds waits for dynamic content loading
• Browser Control: go_back, go_forward for history navigation
• Keyboard Combinations: key_combination supports keyboard shortcuts
• Search Function: search navigates to default search engine

💡 Coordinate System
All coordinates are based on a 1000x1000 grid system, automatically scaled to actual screen size. Recommended screen resolution: 1440x900.

Development Implementation Guide

Environment Setup

from google import genai
from google.genai import types
from google.genai.types import Content, Part
from playwright.sync_api import sync_playwright

# Initialize client
client = genai.Client()

# Configure screen size
SCREEN_WIDTH = 1440
SCREEN_HEIGHT = 900

Basic Configuration

# Configure Computer Use tool
generate_content_config = genai.types.GenerateContentConfig(
    tools=[
        types.Tool(
            computer_use=types.ComputerUse(
                environment=types.Environment.ENVIRONMENT_BROWSER,
                # Optional: exclude specific functions
                excluded_predefined_functions=["drag_and_drop"]
            )
        )
    ]
)

Agent Loop Implementation

def build_agent_loop():
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=False)
        page = browser.new_page()
        
        for iteration in range(10):
            # 1. Send request
            response = client.models.generate_content(
                model='gemini-2.5-computer-use-preview-10-2025',
                contents=contents,
                config=generate_content_config
            )
            
            # 2. Check if completed
            if not has_function_calls(response):
                print(f"Task completed: {response.text}")
                break
            
            # 3. Execute actions
            results = execute_function_calls(response, page, SCREEN_WIDTH, SCREEN_HEIGHT)
            
            # 4. Capture new state
            contents.append(create_feedback(results, page))

Mobile Extension

For mobile applications, custom functions can be added:

def open_app(app_name: str, intent: Optional[str] = None):
    """Open specified app"""
    return {"status": "requested_open", "app_name": app_name}

def long_press_at(x: int, y: int, duration_ms: int = 500):
    """Long press operation"""
    return {"x": x, "y": y, "duration_ms": duration_ms}

def go_home():
    """Return to home screen"""
    return {"status": "home_requested"}

Security Mechanisms and Best Practices

Built-in Security Features

The Gemini 2.5 Computer Use model integrates multi-layer security protection mechanisms:

1. Real-time Safety Checks

• Normal/Allowed: Action is considered safe
• Require Confirmation: Requires explicit user consent before execution

def handle_safety_decision(safety_decision):
    if safety_decision.get("decision") == "require_confirmation":
        user_input = input(f"Safety prompt: {safety_decision['explanation']}\nContinue? (y/n): ")
        return user_input.lower() in ['y', 'yes']
    return True

2. System Instruction Safety

## Safety Rules Example

### Rule 1: User Confirmation (USER_CONFIRMATION)
- Terms Agreement: Prohibit automatic acceptance of terms of service, privacy policies
- Bot Detection: Prohibit automatic CAPTCHA solving
- Financial Transactions: User confirmation required before completing purchases
- Sending Communications: Confirmation needed before sending emails, messages
- Sensitive Information: Authorization required for accessing health, financial records

### Rule 2: Default Behavior (ACTUATE)
- Proactively execute actions not in confirmation category
- Continuously advance user request until completion or encountering limitations

Security Best Practices

1. Secure Execution Environment

   • Use sandboxed virtual machines or containers
   • Dedicated browser profiles with limited permissions

2. Input Sanitization

   • Sanitize user-generated text content
   • Prevent prompt injection attacks

3. Access Control

   • Implement website whitelist/blacklist
   • Limit accessible function scope

4. Monitoring and Logging

   • Log all prompts, screenshots, and actions
   • Maintain detailed audit logs

⚠️ Risk Warning
Gemini 2.5 Computer Use introduces new risk types, including untrusted content, unintended actions, and policy violations. Developers must implement appropriate security measures.

Real-world Use Cases

Enterprise Applications

1. UI Automation Testing

• Google Payment Platform Team: Uses Gemini 2.5 Computer Use to fix fragile end-to-end UI tests
• Results: Successfully fixed over 60% of test execution failures (would have required days of manual fixing)

2. Workflow Automation

• Form Filling: Automate repetitive data entry tasks
• Web Navigation: Collect information across multiple websites
• Application Operations: Execute complex operation sequences in web applications

Third-party Developer Feedback

Poke.com (AI Assistant Service):
"Gemini 2.5 Computer Use far exceeds competitors in speed, typically 50% faster and performing better than the next best solution we considered."

Autotab (AI Agent):
"In reliably parsing context in complex cases, Gemini 2.5 Computer Use surpasses other models, with performance improvements up to 18% in our most difficult evaluations."

Typical Use Scenarios

Pricing and Availability

Pricing Model

• Pricing Standard: Same rates and SKU as Gemini 2.5 Pro
• Cost Monitoring: Can use custom metadata tags to separate Gemini 2.5 Computer Use costs
• Billing Method: Charged by API call volume and processing time

Availability

Access Options

1. Try Now: Visit Browserbase-hosted demo environment
2. Start Building: Check out GitHub reference implementation
3. Join Community: Share feedback in developer forum

✅ Immediately Available
No waiting required, start building Gemini 2.5 Computer Use applications through Gemini API now.

🤔 Frequently Asked Questions

Q: What's the difference between Gemini 2.5 Computer Use model and regular Gemini models?

A: Gemini 2.5 Computer Use is a model specifically optimized based on Gemini 2.5 Pro, with visual understanding and interface operation capabilities. Instead of generating text responses, it generates specific UI operation instructions such as click, type, scroll, etc.

Q: Which platforms and environments are supported?

A: Primarily optimized for web browsers, while also showing excellent performance in mobile UI control. Currently not optimized for desktop operating system-level control.

Q: How to ensure operation safety?

A: The model has built-in multi-layer security mechanisms, including real-time safety checks, user confirmation mechanisms, and system instruction control. Developers should also implement sandboxed environments, access control, and detailed logging.

Q: How does the coordinate system work?

A: Uses a standardized 1000x1000 grid system, automatically scaled to actual screen size. Recommended to use 1440x900 resolution for best results.

Q: Can custom actions be added?

A: Yes, custom functions can be added through function_declarations, while unwanted predefined actions can be excluded through excluded_predefined_functions.

Q: How to handle dynamic content and loading times?

A: The model provides wait_5_seconds action for waiting for dynamic content loading, while supporting intelligent waiting mechanisms based on page state.

Q: How does error handling work?

A: When actions fail or encounter errors, the model analyzes the current screen state and autonomously determines recovery actions. Google internal testing shows over 60% of failed executions can be successfully fixed.

Q: Does it support parallel operations?

A: Supports parallel function calls, where the model can return multiple independent action instructions in a single response, improving execution efficiency.

Summary and Action Recommendations

The Gemini 2.5 Computer Use model represents a major breakthrough in AI agent technology, achieving for the first time direct interaction between AI and graphical user interfaces. Its outstanding performance, comprehensive security mechanisms, and rich application scenarios bring revolutionary possibilities to fields such as automation, testing, and data collection.

Immediate Action Recommendations

1. Quick Experience: Visit Browserbase demo environment to personally experience Gemini 2.5 Computer Use capabilities
2. Technical Exploration: Download GitHub reference implementation to build your first agent in a local environment
3. Community Participation: Join developer forum to exchange experiences and best practices with other developers
4. Security Planning: Develop complete security strategies and testing plans before production deployment

Related Resources

• Official Documentation
• Vertex AI Enterprise Documentation
• GitHub Reference Implementation
• Developer Community Forum

The release of the Gemini 2.5 Computer Use model marks the entry of AI agents into a completely new development stage. Start exploring this technology now and seize the opportunity in AI automation applications!

Gemini 2.5 Computer Use Guide