CALIFORNIA / RankWire.AI / – Google has revealed its latest flagship artificial intelligence system, Gemini 4 Argon, designed specifically for demanding professional workloads. The company announced this model on Sept. 30, marking the beginning of its Gemini 4 series. Argon is tailored for fields such as software engineering, finance, legal analysis, and cybersecurity defense. Google highlighted that this model can perform deeper reasoning across lengthy, multi-step tasks. Currently, access is limited to a select group of cybersecurity experts participating in its Fairwind Program.
With Gemini 4 Argon, the maximum token output has been increased to 1 million, up from the previous limit of 64,000 tokens. This enhancement allows the model to handle extended tasks within a single processing session. The initial API pricing is set at $2 per million input tokens and $10 per million output tokens. Input tokens that are cached qualify for a 95% discount. After the introductory phase, the prices will increase to $4 and $20, respectively.
Google shared that thousands of its employees are already utilizing Argon for specialized coding, research, and writing projects. Internal teams have also employed the model for tasks like memory optimization in data centers and large-scale code migrations. One project involved using Argon agents for C and C++ migrations to Rust. Another applied agents to memory profiling across Google’s data centers. Google reported that these optimizations freed over 300 tebibytes of memory, with additional savings identified through similar efforts.
Enhanced Capacity for Advanced Professional Tasks
Google announced that Gemini 4 Argon scored 77.9% on DeepSWE v1.1, a benchmark evaluating software engineering performance over long durations. The company also highlighted its results in finance, legal work, and automation testing. Argon supports multimodal reasoning alongside coding and enterprise tasks. The model is part of Google DeepMind’s broader Gemini family. According to Google, the increased output capacity enables Argon to manage longer workflows that involve multiple reasoning and execution steps.
Cybersecurity applications are also a key focus during the initial deployment phase. Google stated that Argon can identify, validate, and patch software vulnerabilities in controlled defensive environments. Wiz is utilizing Argon through its Scan for Good initiative, which aims to detect security vulnerabilities in public infrastructure. The company reported that Argon achieved a score of 68% on CWE-bench v1, a benchmark for vulnerability remediation. Selected defenders are gaining access to Argon without the usual cyber guardrails to perform targeted defensive tasks.
Limited Release Before a Broader Gemini 4 Rollout
Google has not yet announced a specific date for the full public launch of Gemini 4 Argon. The company explained that it is adopting a phased approach and collecting feedback from early testers. It is also participating in a voluntary U.S. government process for pre-release model access. Future releases are expected to include developers, enterprises, and consumers. The rollout will begin with paid API users and Google AI Ultra subscribers, although no fixed launch date has been provided for these groups.
Additionally, Google confirmed that it has no plans to release Gemini 3.5 Pro, which was originally scheduled for June. This decision positions Gemini 4 Argon as the company’s latest flagship AI model optimized for demanding reasoning and professional workflows. The company continues to offer other Gemini models catering to various performance and budget needs. Argon distinguishes itself with its larger output capacity, advanced coding capabilities, and specialized cybersecurity functions. Currently, access remains limited to trusted testers and select security partners engaged in defense efforts.