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What is Genie 4?

Genie 4 is an advanced generative world model developed by Google DeepMind to create interactive, photorealistic virtual environments that respond dynamically to user actions and natural language instructions. The model generates visual scenes in real time, allowing users to explore simulated worlds through keyboard navigation and camera controls. Its multimodal architecture combines visual generation, native audio synthesis, physical simulation, and human behavior modeling within a continuously evolving environment. Genie 4 can simulate physical phenomena such as aerodynamics, collisions, object movement, and environmental interactions to create more realistic virtual experiences. Its human simulation capabilities generate characters that move naturally, respond to their surroundings, and participate in interactive dialogue. Native audio generation produces environmental sounds such as wind, water, footsteps, and spoken conversations that correspond to events within the simulated world. Users can modify ongoing simulations by changing weather conditions, introducing objects, adding characters, and adjusting camera perspectives through natural language prompts. Integration with Gemini Omni helps ground generated environments in realistic appearances and behaviors, while Gemini 3.8 Flash provides reasoning capabilities for planning and coordinating multistep events. The model can support autonomous agent development and robotics research by generating varied environments in which AI systems can practice navigation, decision-making, and task execution. Additional applications include interactive game prototyping, film previsualization, historical scene reconstruction, educational experiences, and engineering simulations.

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

Gemini
Gemini Enterprise
Google AI Studio

Integrations Supported

Gemini
Gemini Enterprise
Google AI Studio
Android Studio
C
C#
Cheaper Inference
Gemini 3.5 Flash Cyber
Gemini 3.8 Flash Cyber
Gemini 3.8 Live
Google
Google AI Mode
Google AI Overviews
Model Context Protocol (MCP)
OfoxAI
Ruby
Rust
SQL
Swift
YAML

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

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

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

deepmind.google/

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.com

Categories and Features

AI Models

Not specified

AI World 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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