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What is Gemini 4 Flash?

Gemini 4 Flash, reportedly codenamed Hydrogen, is a potential next-generation multimodal artificial intelligence model in Google DeepMind's Gemini family. The model is expected to follow Google's established Flash series, which emphasizes efficient processing and relatively low-latency inference for a broad range of AI applications. Google's existing Flash models support natural language understanding, programming assistance, reasoning, and multimodal analysis across different types of information. Hydrogen could provide similar capabilities for text generation, document summarization, content classification, and technical problem-solving. Potential multimodal functionality may include understanding images, audio recordings, video content, and complex documents. Software development applications could include code generation, debugging, technical documentation, and assistance with automated programming workflows. The model might also support tool calling and structured outputs for applications that require reliable communication with external systems. Long-context processing could enable analysis of extensive documents, source code repositories, and information collected during multistep tasks. Enterprise use cases may include customer support automation, business intelligence, information extraction, and AI-powered productivity applications. Based on Google's existing developer ecosystem, a future release could be distributed through Google AI Studio, the Gemini API, and Vertex AI. Google has not officially confirmed the Hydrogen codename, architecture, supported input types, context window, performance benchmarks, pricing, or release date.

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.

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Integrations Supported

Antigravity CLI
Bash
Bind AI
C
Cursor
Dart
Factory Droid
Gemini Enterprise Agent Platform
Go
Google
Google AI Overviews
HTML
JetBrains Junie
Kotlin
OfoxAI
PowerShell
Rust
Swift
Vercel AI Gateway
Wikis.ai

Integrations Supported

Antigravity CLI
Bash
Bind AI
C
Cursor
Dart
Factory Droid
Gemini Enterprise Agent Platform
Go
Google
Google AI Overviews
HTML
JetBrains Junie
Kotlin
OfoxAI
PowerShell
Rust
Swift
Vercel AI Gateway
Wikis.ai

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

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.com

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.com

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

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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