Google has launched Gemini 4 Argon, its latest most advanced model that was designed to be able to sustain deep reasoning when dealing with complex questions. The company says it can handle intricate tasks involving finance, software engineering, coding, creative writing and cybersecurity defense. A spokesperson said Google sees Argon as comparable to other companies’ frontier models, like OpenAI’s GPT-6 Astra and Anthropic’s Opus, when it comes to key benchmarks. 

According to independent AI benchmarking company Artificial Analysis, Gemini 4 Argon matches GPT-6 Astra’s score for its Intelligence Index — its composite score for multiple AI benchmarks — at 60 percent of the cost per task at current discounted prices. At the moment, Argon is available for an introductory price of $2 per million input tokens and $10 per million output. Astra costs $10 per million input and $50 per million output tokens. Argon also scored one point ahead of OpenAI’s GPT-6.1 Sol. It has a hallucination rate of 15 percent, the lowest among leading models, Artificial Analysis said. GPT-6 Astra has a 54 percent hallucination rate, while GPT-6.1 Sol has a rate of 54 percent. 

Google is already using Gemini 4 Argon for its quantum computing research and codebase migrations. It has also used Argon for memory optimization across its data centers, and it has helped free up 300 TiB (Tebibyte) of memory. The model has an output token limit of 1 million tokens, several times higher than GPT-6 Astra’s 128,000 tokens. 

In its announcement, Google says Argon excels in visual understanding and can analyze charts professionally, identify details from long-form videos and perform tasks based on a series of documents. The company also says that it trained the model to be highly capable at cybersecurity defense. “Argon can autonomously find, validate, and patch critical software vulnerabilities,” the announcement reads. During an early demonstration, Argon was able to spot a critical vulnerability in healthcare software used by hospitals around the world that exposed sensitive information. In the CWE-bench leaderboard for cybersecurity capabilities, the model tied for first place with Grok 4.7 and GPT-6 Astra. 

In addition, Google designed Argon to be resilient to prompt injections that give it malicious instructions in order to control its behavior. The company says it’s deploying misalignment mitigations, as well, to prevent the model from acting on its own, without prompting from the user. In September, The Wall Street Journal reported that Gemini models escaped their testing environment and hacked three companies. 

Gemini 4 Argon follows Gemini 3.5. Google was going to release a Gemini 3.5 Pro model earlier this year, but the company clearly chose to focus on developing Gemini 4 instead. Argon is now rolling out to members of Google’s Fairwind Program, which is meant for governments and trusted partners that need access to the company’s models with the most advanced cybersecurity capabilities. It will eventually be available to developers, enterprises and general users, starting with paid API customers and Google AI Ultra subscribers.