Gemini Reviews & Ratings

Gemini

5.0 out of 5 stars
Gemini 4 Argon Reviews & Ratings

Gemini 4 Argon

5.0 out of 5 stars

Ratings and Reviews 2 Ratings

Total 5 out of 5 stars
ease 5 out of 5 stars
features 4.5 out of 5 stars
design 4 out of 5 stars
support 4.5 out of 5 stars

Ratings and Reviews 1 Rating

Total 5 out of 5 stars
ease 5 out of 5 stars
features 5 out of 5 stars
design 5 out of 5 stars
support 5 out of 5 stars

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What is Gemini?

Gemini is Google’s next-generation AI assistant designed to deliver intelligent help across research, creativity, communication, and task management. Built on Google’s most advanced AI models, including Gemini 3, it helps users understand complex topics, generate content, and solve problems through natural conversation. Gemini enables text, image, and video generation, allowing users to quickly turn ideas into visual and written outputs. Its grounding in Google Search ensures responses are informed, relevant, and easy to explore further through follow-up questions. Gemini supports hands-free and conversational brainstorming through Gemini Live, making it useful for presentations, interviews, and idea development. With Deep Research, Gemini can analyze hundreds of sources and compile detailed reports in a fraction of the time. The platform connects directly to Google apps like Gmail, Docs, Calendar, Maps, and YouTube to streamline everyday workflows. Users can build personalized AI helpers using Gems by saving detailed instructions and uploaded files. Gemini’s long context window allows it to process large documents, code repositories, and research materials in a single session. Multiple plans provide flexibility, from free access for students and casual users to premium tiers with higher limits and advanced features. Gemini is available across web and mobile devices for seamless access. Designed to adapt to different needs, Gemini supports consumers, professionals, educators, and enterprises alike.

What is Gemini 4 Argon?

Gemini 4 Argon is Google's frontier AI model for advanced reasoning and long-horizon workflows across software engineering, enterprise knowledge work, cybersecurity defense, and creative tasks. The model combines coding, multimodal understanding, reasoning, and multi-step execution to address complex professional workloads that may require sustained work across many steps. Google expanded Argon's maximum output from 64,000 tokens to 1 million tokens, allowing it to reason and generate hundreds of thousands of tokens within a single trajectory when required. Google engineers are already using Argon internally for tasks ranging from everyday debugging and algorithm design to large-scale migrations of C and C++ codebases to Rust. On DeepSWE v1.1, which evaluates real-world long-horizon software engineering, Google reports that Gemini 4 Argon achieves a score of 77.9%. The model also scored 51.3% on AutomationBench, a Zapier benchmark measuring end-to-end execution across business functions. Its knowledge-work capabilities include financial research, legal research and drafting, professional chart analysis, document-based workflows, and long-video understanding, with a reported 91.7% score on LVBench. Google has additionally trained Argon for defensive cybersecurity, enabling it to autonomously find, validate, and patch critical software vulnerabilities. Argon tied for first with a reported 68% score on CWE-bench v1 and has been evaluated on vulnerability discovery across complex codebases covering 20 programming languages. Google is using a phased release strategy that begins with trusted cyber defenders through the Fairwind Program while additional safeguards are tested before broader availability. The company plans to expand Gemini 4 Argon to developers, enterprises, and consumers, beginning with paid API customers and Google AI Ultra subscribers.

Media

Media

Integrations Supported

C
C++
Gemini 3.5 Flash
Gemini 3.5 Flash Cyber
Gemini 3.8 Live
Gemini Computer Use
Gemini Enterprise
Gemini Managed Agents
Go
Google
Google AI Overviews
Google AI Ultra
JavaScript
Model Context Protocol (MCP)
Python
R
Ruby
Rust
SQL
Wikis.ai

Integrations Supported

C
C++
Gemini 3.5 Flash
Gemini 3.5 Flash Cyber
Gemini 3.8 Live
Gemini Computer Use
Gemini Enterprise
Gemini Managed Agents
Go
Google
Google AI Overviews
Google AI Ultra
JavaScript
Model Context Protocol (MCP)
Python
R
Ruby
Rust
SQL
Wikis.ai

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$2 per 1M tokens (input)
$2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price.

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.google.com

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.com

Categories and Features

AI Art Generators

Not specified

AI Assistants

Not specified

AI Code Generators

Not specified

AI Coding Models

Not specified

AI Image Generators

Not specified

AI Models

Not specified

AI Writing

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

LLM API

Not specified

Multimodal Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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