Google releases Gemini 4 Argon AI model
Google DeepMind: Gemini 4 Argon: Built to solve your hardest problems
The new model aims to handle complex reasoning tasks where current systems often struggle or fail completely.
What happened
Google has launched Gemini 4 Argon, a new AI model designed to handle complex reasoning tasks across coding, finance, legal, cybersecurity, and science. The model is available globally through an API, the Gemini app, and Google Antigravity, with access tiered by subscription level and introductory pricing of $2 per million input tokens and $10 per million output tokens. Early users at Google and other organizations have used Argon to complete engineering tasks faster, including large codebase refactoring and business workflow optimization.
What each outlet adds
- Google DeepMind ↗: Argon ranks first on the Vals Index, which measures performance across critical economic sectors.
- The Verge ↗: Google had fallen behind rivals in recent months, and this is the company's first major frontier model release since late 2025.
- Ars Technica ↗: Google initially delayed Argon's release due to concerns about potential misuse but has deployed safeguards including automated monitoring to detect unintended workflows.
- The Decoder ↗: Argon trails Anthropic's Claude Opus 5.5 and Meta's Muse Wonder Full in independent benchmarks, and Google is offering free access to 10,000 researchers for six months.
Why it matters
The arrival of multiple frontier models from different companies in quick succession demonstrates how rapidly the competitive landscape in AI development is shifting. Google's release represents the company's effort to catch up after falling behind rivals in the frontier AI race.
Get smart on it
Gemini 4 Argon is a frontier AI model released for global access to developers, enterprises, and consumers through various platforms and subscription tiers. The model is designed to handle complex, multi-step tasks across domains including coding, finance, legal, cybersecurity, and science, and ranks first on the Vals Index, which measures performance across critical economic sectors. Early users at Google and other organizations have used Argon to complete engineering tasks faster, including large codebase refactoring, business workflow optimization, cybersecurity vulnerability patching, and research breakthroughs in quantum computing and life sciences. The model is available at an introductory price of $2 per million input tokens and $10 per million output tokens.
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