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What is Gemini 4 Carbon?

Gemini 4 Carbon is a reportedly experimental large language model under development at Google DeepMind as part of the company's Gemini 4 artificial intelligence research efforts. The model has been identified in reporting about internal testing of multiple Gemini 4 variants, including Argon, Barium, and Carbon. Carbon has reportedly appeared within Google's internal Jetski coding platform, where employees can evaluate AI models for software development tasks. Internal feedback cited in reporting has suggested promising performance in advanced programming applications, although these observations have not been independently validated through published benchmarks. The model's development is associated with Google's efforts to improve AI reasoning, code generation, and assistance with complex software engineering workflows. Potential applications include debugging, code modification, technical analysis, and automated execution of multistep development tasks. Carbon may also be evaluated for autonomous coding workflows in which AI systems plan changes, interact with development tools, and assist with software maintenance. The publicly released Gemini 4 Argon model provides a reference point for Google's broader work on long-context reasoning, multimodal understanding, and agentic software engineering. However, Carbon's specific architecture, supported input modalities, context window, training methods, and tool integration capabilities have not been publicly documented. Google has not confirmed whether Carbon will launch as a separate model, replace an existing Gemini variant, or remain an internal research system. Commercial availability, API access, pricing, licensing, and official performance benchmarks have not been announced.

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
Bind AI
C
C#
C++
Cursor
Gemini 3.5 Flash-Lite
Gemini 3.8 Flash Cyber
Gemini Enterprise Agent Platform
Gemini Spark
Google AI Overviews
Hermes Agent
Kotlin
Kubernetes
OfoxAI
OpenClaw
Scala
Solidity
Swift
YAML

Integrations Supported

Antigravity CLI
Bind AI
C
C#
C++
Cursor
Gemini 3.5 Flash-Lite
Gemini 3.8 Flash Cyber
Gemini Enterprise Agent Platform
Gemini Spark
Google AI Overviews
Hermes Agent
Kotlin
Kubernetes
OfoxAI
OpenClaw
Scala
Solidity
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

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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