CALIFORNIA / RankWire.AI / – Google has unveiled Gemini 4 Argon, its latest flagship AI model designed for sophisticated professional applications. Announced on Sept. 30, Argon is positioned at the forefront of the Gemini 4 series, supporting intricate software development, financial analysis, legal research, and cybersecurity operations. The model also excels in processing extended sequences of reasoning and execution. Currently, access remains restricted, with select cybersecurity professionals utilizing Argon through the Fairwind Program.
The maximum token output capacity for Argon has been increased to 1 million, a significant jump from the prior limit of 64,000 tokens. This enhancement enables the model to handle more extensive tasks without splitting work into multiple sessions. Initial API pricing starts at $2 per million input tokens, with output tokens costing $10 per million during the same period. Inputs stored in cache benefit from a 95% discount. Future pricing will shift to $4 for input tokens and $20 for output tokens.
Numerous employees within the company are already leveraging Argon for coding, research, and writing projects. Internal teams have evaluated the model on data center optimization and large-scale software migrations. One particular initiative involved using Argon agents to facilitate C and C++ migrations to Rust. Another focused on memory profiling across data centers, resulting in the release of over 300 tebibytes of freed memory. Additional savings have been identified through ongoing analysis of the same systems.
Enhanced capacity for complex technical tasks
Google reported a 77.9% score for Argon on DeepSWE v1.1, a benchmark assessing long-term software engineering performance. The company has also published results related to finance, legal work, automation, and multimodal tasks. Argon was developed by Google DeepMind as part of the broader Gemini model family, which combines coding tools with long-context reasoning and multimodal functionalities. Its expanded output capacity supports workflows that involve numerous interconnected steps before reaching completion.
Cybersecurity continues to be a core focus during the initial deployment. Argon can identify, verify, and patch vulnerabilities in approved defensive environments. Through its Scan for Good initiative, Wiz is utilizing the model to detect security flaws in public infrastructure. Google reported a 68% score on CWE-bench v1, a benchmark dedicated to vulnerability remediation. Selected security teams can also operate Argon without standard cyber guardrails on approved defensive security projects.
Limited public rollout planned in stages
A specific launch date for broad public access to Gemini 4 Argon has not yet been announced by Google. The company is employing a phased approach, collecting feedback from early testers, and participating in a voluntary U.S. government process that grants pre-release access to advanced AI models. Later, the model will be available to developers, enterprise clients, and consumers. Priority access is expected for paid API users and Google AI Ultra subscribers, although an exact launch date remains unconfirmed.
Google has also clarified that Gemini 3.5 Pro will not be released. This model was previously anticipated before the launch of Gemini 4. Currently, Argon represents the company’s newest flagship offering for intensive reasoning and professional workloads. Other Gemini variants continue to be available, catering to different performance needs and price points. For now, Gemini 4 Argon is primarily accessible to trusted testers, cybersecurity partners, and early-access programs, with wider availability still in the planning stages.