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Description

Gemini 3 Pro is a next-generation AI model from Google designed to push the boundaries of reasoning, creativity, and code generation. With a 1-million-token context window and deep multimodal understanding, it processes text, images, and video with unprecedented accuracy and depth. Gemini 3 Pro is purpose-built for agentic coding, performing complex, multi-step programming tasks across files and frameworks—handling refactoring, debugging, and feature implementation autonomously. It integrates seamlessly with development tools like Google Antigravity, Gemini CLI, Android Studio, and third-party IDEs including Cursor and JetBrains. In visual reasoning, it leads benchmarks such as MMMU-Pro and WebDev Arena, demonstrating world-class proficiency in image and video comprehension. The model’s vibe coding capability enables developers to build entire applications using only natural language prompts, transforming high-level ideas into functional, interactive apps. Gemini 3 Pro also features advanced spatial reasoning, powering applications in robotics, XR, and autonomous navigation. With its structured outputs, grounding with Google Search, and client-side bash tool, Gemini 3 Pro enables developers to automate workflows and build intelligent systems faster than ever.

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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Gemini Yes 
Gemini Enterprise Yes 
Gemini Enterprise Agent Platform Yes 
Google AI Studio Yes 
Python Yes 
Anara Yes 
C Yes 
F# Yes 
GitHub Yes 
Google AI Mode Yes 
Java Yes 
Julia Yes 
OpenCode Yes 
Oz Yes 
R Yes 
SQL Yes 
Sup AI Yes 
Transor Yes 
TypeScript Yes 
Use AI Yes 

Integrations

Gemini Yes 
Gemini Enterprise Yes 
Gemini Enterprise Agent Platform Yes 
Google AI Studio Yes 
Python Yes 
Anara No 
C No 
F# No 
GitHub No 
Google AI Mode No 
Java No 
Julia No 
OpenCode No 
Oz No 
R No 
SQL No 
Sup AI No 
Transor No 
TypeScript No 
Use AI No 

Pricing Details

$19.99/month
$2 per million tokens (input)
$12 per million tokens (output)
Free Trial No 
Free Version No 

Pricing Details

$0.15 per 1M input tokens
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

deepmind.google/models/gemini/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

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

Product Features

Alternatives

Alternatives