Google has released Gemini 4 Argon, a new frontier AI model available to developers and enterprises. The company says the model excels in complex tasks across coding, finance, and science.
Google has made its latest frontier AI model, Gemini 4 Argon, globally available to developers, enterprises, scientists, and consumers. The release, announced on October 13, 2026, provides access via the API in AI Studio and the Gemini platform, as well as through Google AI Ultra and Pro subscriptions in the Gemini app and AI Mode in Search.
The model launches with an introductory price of $2 per million input tokens and $10 per million output tokens. According to Google, cached input tokens are discounted by 95%.
Google states that Gemini 4 Argon is designed for deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science. The company says the model ranks #1 on the Vals Index, a benchmark that measures model performance across critical economic sectors such as finance, coding, legal, and tax work.
Google reports that internal teams and early access partners have used Argon to address significant engineering and business challenges. In Google’s Chrome team, the model assisted in separating core webpage handling from a legacy folder of browser features within Chromium’s 40 million-line codebase. Google says this helped complete an architectural refactor across hundreds of files in weeks rather than months.
For the open-source Agent Development Kit (ADK), Google says Argon helped cut in-memory session prep time by 40% in long sessions and sped up cold imports by 21%. Additionally, Google reports that using Argon achieved a 2.85x end-to-end inference speedup on an A100 for its open Gemma models.
Enterprise partners have also provided feedback on the model's performance. Alex Cabrera, Founding Engineer at Axiom Bio, stated, "Gemini 4 represents a step change in what AI can accomplish in real-world science. We've seen it reason through complex experimental data, from cellular imaging to mass spectrometry, and make subtle findings that traditionally require expert scientists to identify."
Gopal Srinivasan, Global AI and Data Lead at Deloitte, noted, "Early impressions from Gemini 4 are very strong: for long-running tasks across these workflows, it completed successfully 100% of the time in our evals, maintaining context and running through multiple tools across impressive spans."
Google highlights several scientific breakthroughs attributed to the use of Gemini 4 Argon. In quantum computing, the company says the model helped translate an internal version of AlphaQubit, a machine learning quantum error correction decoder, into a highly optimized hardware kernel, nearly doubling its inference throughput.
In nuclear fusion research, a team at Google alongside Professor Matt Landreman of the University of Maryland discovered a broader class of counterexamples to "Grad’s conjecture," a long-standing hypothesis regarding mathematical solutions for stellarator magnetic fields.
In cybersecurity, Google announced an expansion of the Fairwind Program to hundreds of additional partners. Wiz, a cybersecurity company, used Argon for its "Scan for Good" initiative. Google reports that Wiz used the model to identify and remediate a gap that risked exposing sensitive government data and to protect healthcare infrastructure by discovering a public file download bypass.
The release of Gemini 4 Argon represents a significant update to Google's AI capabilities, with the company positioning the model as a tool for high-stakes professional workflows in science, law, and engineering. By offering free access to 10,000 scientists for six months and integrating the model into enterprise tools, Google aims to accelerate research and development across multiple industries. The reported improvements in coding efficiency and scientific discovery suggest a potential shift in how complex technical problems are approached in both corporate and academic settings.
Sources
This article was drafted with AI assistance and checked against the sources above. Company claims are reported as claims. Cover image is AI-generated.
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