Google announced Gemini 4 Argon on September 30, a frontier model built to sustain deep reasoning across complex, long-horizon workflows in software engineering, finance, law, and cybersecurity defense.
Argon is not yet broadly available. It is rolling out first to trusted cyber defenders through the Fairwind Program, while Google participates in the U.S. government’s voluntary pre-release model access process. Paid API customers and Google AI Ultra subscribers will be first in line for the general release, though Google has not provided a specific date.
Argon launches with introductory pricing of $2 per million input tokens and $10 per million output tokens (discounted by 95% for cached inputs), which will eventually rise to $4 and $20. Google also expanded the model’s maximum output limit from 64,000 tokens to 1 million. According to independent firm Artificial Analysis, Argon matches GPT-6 Astra on its Intelligence Index at 60% of the cost per task at these introductory rates.
Google is already deploying Argon internally. In quantum computing research, the model beat a published optimization baseline by 40%, and in infrastructure, it identified memory optimizations capable of saving up to 1 PiB across Google data centers. Argon agents are also migrating legacy C/C++ code to Rust: in the libgav1 video decoder, they replaced 32,000 lines of SIMD code with Rust that executes 2.7 times faster than previous manual ports.
On security, Argon can autonomously find, validate, and patch critical vulnerabilities—including a previously undiscovered flaw in healthcare software that exposed patient data across global hospitals. Google also plans to offer a dedicated version without cyber guardrails specifically for trusted defenders and internal safety teams.
As industry momentum shifts toward personal agents, Google’s product chief confirmed the company is exploring integrating Argon to power complex, multi-step tasks within its Spark platform.