Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Gemini Computer Use is an agentic computer interaction capability built into Gemini 3.5 Flash. It enables developers and enterprises to create AI agents that can work across browser, desktop, and mobile environments by seeing interfaces, reasoning through tasks, and taking action. The capability was previously offered through a standalone Gemini 2.5 computer use model, but is now natively integrated into Gemini 3.5 Flash. This gives developers access to stronger performance for agentic computer use tasks while also combining with Gemini’s existing strengths in function calling, Search grounding, Maps grounding, and built-in tools. Gemini Computer Use is designed for long-horizon automation, continuous software testing, enterprise knowledge work, and workflows that span multiple professional applications. Developers can start building with the feature through the Gemini API or Gemini Enterprise Agent Platform. Google also provides a demo environment through Browserbase for testing the capability. Safety controls include targeted adversarial training for live-environment risks, optional explicit user confirmation for sensitive or irreversible actions, and automatic task stopping when indirect prompt injection is identified. Gemini Computer Use helps organizations build practical AI agents that can complete complex digital tasks while supporting sandboxing, human review, and strict access controls.

Description

The Gemini Embedding's inaugural text model, known as gemini-embedding-001, is now officially available through the Gemini API and Gemini Enterprise Agent Platform, having maintained its leading position on the Massive Text Embedding Benchmark Multilingual leaderboard since its experimental introduction in March, attributed to its outstanding capabilities in retrieval, classification, and various embedding tasks, surpassing both traditional Google models and those from external companies. This highly adaptable model accommodates more than 100 languages and has a maximum input capacity of 2,048 tokens, utilizing the innovative Matryoshka Representation Learning (MRL) method, which allows developers to select output dimensions of 3072, 1536, or 768 to ensure the best balance of quality, performance, and storage efficiency. Developers are able to utilize it via the familiar embed_content endpoint in the Gemini API.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Gemini 3.5 Flash
Python

Integrations

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Gemini 3.5 Flash
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0.15 per 1M input tokens
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

gemini.google.com

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

developers.googleblog.com/en/gemini-embedding-available-gemini-api/

Product Features

Alternatives

Lux Reviews

Lux

OpenAGI Foundation

Alternatives

Agent S Reviews

Agent S

Simular