Gemini 4 Argon Reviews

Gemini 4 Argon

5.0 out of 5 stars

Average Ratings 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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features 0 out of 5 stars
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Description

Gemini 4 Argon is a frontier AI model from Google DeepMind built to sustain deep reasoning across complex, long-running professional workflows. Google designed the model for demanding work spanning software engineering, finance, legal tasks, enterprise knowledge work, cybersecurity defense, and creative writing. Argon supports coding, reasoning, multimodality, and multi-step task execution, allowing it to work across workflows that require information gathering, analysis, tool use, and extended problem solving. Its output token limit has been increased from 64,000 to 1 million tokens, giving the model additional capacity for lengthy reasoning and generation within a single trajectory. On DeepSWE v1.1, Google reports a score of 77.9% for real-world long-horizon software engineering, while its AutomationBench score of 51.3% measures performance on end-to-end business workflows. Google also reports strong results on evaluations covering finance, legal work, visual analysis, and long-video understanding, including a 91.7% score on LVBench. For cybersecurity teams, Argon can autonomously discover, validate, and patch software vulnerabilities and achieved a reported 68% score on CWE-bench v1. Google is initially providing the model to selected cyber defenders through its Fairwind Program while strengthening safeguards before expanding access to developers, enterprises, and consumers. Argon is planned to launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens receiving a 95% discount from the standard input price.

Description

Inkling 2 Small is a general-purpose multimodal AI model developed by Thinking Machines Lab for software engineering, advanced reasoning, visual analysis, and autonomous agent applications. The model features a sparse mixture-of-experts architecture containing 594 billion total parameters, with approximately 17 billion parameters activated during inference. Its one-million-token context window supports processing large documents, software repositories, extended conversations, and complex collections of information. Inkling 2 Small accepts text and image inputs and generates text outputs, enabling visual reasoning, programming assistance, document analysis, and multimodal problem-solving. Its agentic coding capabilities support autonomous software development, code debugging, repository modifications, application creation, and verification of completed engineering tasks. The model can also perform extended research workflows involving machine learning experimentation, GPU kernel optimization, data analysis, and iterative scientific problem-solving. Configurable reasoning effort allows users to balance response speed and computational resources against the complexity of individual tasks. Thinking Machines Lab reports benchmark scores of 25.4% on FrontierCode 2.0, 72.1% on DeepSWE 1.1, and 86.3% on SWE-Bench Pro v2 Hard. Inkling 2 Small is available for inference and fine-tuning through Tinker, with model weights scheduled for release under the Apache 2.0 license after additional safety evaluations.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Model Context Protocol (MCP) Yes 
.NET Yes 
C Yes 
C++ Yes 
Dart Yes 
Gemini 3.5 Flash Yes 
Gemini 3.5 Flash-Lite Yes 
Gemini 3.8 Flash Cyber Yes 
Gemini Enterprise Yes 
Gemini Managed Agents Yes 
Google AI Plus Yes 
Hermes Agent Yes 
Kotlin Yes 
Kubernetes Yes 
Objective-C Yes 
OpenClaw Yes 
Rust Yes 
Tinker No 
Wikis.ai Yes 
YAML Yes 

Integrations

Model Context Protocol (MCP) Yes 
.NET No 
C No 
C++ No 
Dart No 
Gemini 3.5 Flash No 
Gemini 3.5 Flash-Lite No 
Gemini 3.8 Flash Cyber No 
Gemini Enterprise No 
Gemini Managed Agents No 
Google AI Plus No 
Hermes Agent No 
Kotlin No 
Kubernetes No 
Objective-C No 
OpenClaw No 
Rust No 
Tinker Yes 
Wikis.ai No 
YAML No 

Pricing Details

$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.
Free Trial No 
Free Version No 

Pricing Details

$0.30 per million input tokens
$0.30 per million input tokens, $0.03 per million cached input tokens, and $1.00 per million output 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 No 
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 No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

gemini.com

Vendor Details

Company Name

Thinking Machines Lab

Founded

2025

Country

United States

Website

thinkingmachines.ai/

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