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Description

The overwhelming amount of information available poses a significant challenge to advancements in science. With the rapid expansion of scientific literature and data, pinpointing valuable insights within this vast sea of information has become increasingly difficult. Nowadays, people rely on search engines to access scientific knowledge, yet these tools alone cannot effectively categorize and organize this complex information. Galactica is an advanced language model designed to capture, synthesize, and analyze scientific knowledge. It is trained on a diverse array of scientific materials, including research papers, reference texts, knowledge databases, and other relevant resources. In various scientific tasks, Galactica demonstrates superior performance compared to existing models. For instance, on technical knowledge assessments involving LaTeX equations, Galactica achieves a score of 68.2%, significantly higher than the 49.0% of the latest GPT-3 model. Furthermore, Galactica excels in reasoning tasks, outperforming Chinchilla in mathematical MMLU with scores of 41.3% to 35.7%, and surpassing PaLM 540B in MATH with a notable 20.4% compared to 8.8%. This indicates that Galactica not only enhances accessibility to scientific information but also improves our ability to reason through complex scientific queries.

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.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

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Screenshots View All

Integrations

Agent Search on Gemini Enterprise Agent Platform No 
Antigravity CLI No 
Bind AI No 
CSS No 
Dart No 
Gemini 3.5 Flash No 
Gemini 3.5 Flash-Lite No 
Gemini Enterprise No 
Gemini Enterprise Agent Platform No 
Go No 
Google AI Overviews No 
Google AI Studio No 
Hermes Agent No 
Java No 
Offloop No 
PowerShell No 
Python No 
Swift No 
TypeScript No 
Wikis.ai No 

Integrations

Agent Search on Gemini Enterprise Agent Platform Yes 
Antigravity CLI Yes 
Bind AI Yes 
CSS Yes 
Dart Yes 
Gemini 3.5 Flash Yes 
Gemini 3.5 Flash-Lite Yes 
Gemini Enterprise Yes 
Gemini Enterprise Agent Platform Yes 
Go Yes 
Google AI Overviews Yes 
Google AI Studio Yes 
Hermes Agent Yes 
Java Yes 
Offloop Yes 
PowerShell Yes 
Python Yes 
Swift Yes 
TypeScript Yes 
Wikis.ai Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

Deployment

Web-Based Yes 
On-Premises Yes 
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 No 

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

Meta

Founded

2004

Country

United States

Website

meta.com

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

gemini.com

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