AI News
Gemini 4 Argon is now globally available
Google AI released Gemini 4 Argon globally for developers, enterprises, and consumers. The model is priced at $2 per million input tokens and $10 per million output tokens, with
What this piece is grounded in
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Gemini 4 Argon is now globally available today for developers and enterprises via the API in AI Studio and Gemini platform
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The model launches today at an introductory price of $2 per million input tokens and $10 per million output tokens
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Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science
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ranking #1 on the Vals Index, which measures model performance across critical economic sectors like finance, coding, legal, and tax work
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What changed
Google AI announced that Gemini 4 Argon is now globally available today for developers and enterprises via the API in AI Studio and Gemini platform, for Google AI Ultra subscribers in Google Antigravity, and Google AI Ultra and Pro subscribers in the Gemini app and AI Mode in Search. The model launches at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens at 95% off. According to the source, Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science.
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Why it matters for practical AI work
The source reports that Argon's depth and precision across multi-step tasks leads it to outperform other frontier models on benchmarks across domains, ranking #1 on the Vals Index, which measures model performance across critical economic sectors like finance, coding, legal, and tax work. At Google, software engineers have been shipping high-quality code faster than ever, with Argon in Antigravity helping teams increase agentic code submissions by more than 35% while reducing code rollbacks by nearly a third. The source also describes Argon synthesizing ~50 GB of Airborne LiDAR scans, GIS room vectors, Library of Congress CAD drawings, and NPS archives to reconstruct 3D models of Chaco Canyon.
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What you can verify
The source story from Google AI provides specific examples of Argon's use, including building a detailed model of a Pagoda using multi-agent visual critique loops in Antigravity, turning pictures of a real desk into a playable miniature racing game, and writing Python scripts to procedurally sculpt, rig, animate, and PBR-bake a complex 3D game. The source also mentions that at Isomorphic Labs, the team is using Argon to accelerate drug discovery and design research workflows, reducing a process that typically takes weeks into hours. The model is available to try in Google AI Studio, according to the source.
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What remains unclear
The supplied feed entry is a concise summary; consult the canonical article for full context. The source text does not provide details on the model's parameter count, training data, or specific benchmark scores beyond the Vals Index ranking. The source also does not specify the duration of the introductory pricing or any future price changes. Additionally, the source mentions expansion to hundreds of additional Fairwind Program partners starting today, but does not list which partners are included or the full scope of that program.
Questions readers ask
What is the introductory pricing for Gemini 4 Argon?
According to the Google AI source, Gemini 4 Argon launches at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens at 95% off. This pricing applies to the API in AI Studio and Gemini platform, as stated in the source.
Which domains does Gemini 4 Argon excel in?
The source states that Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science. It also ranks #1 on the Vals Index, which measures model performance across critical economic sectors like finance, coding, legal, and tax work, according to the source.