Google DeepMind announced Gemini 4 Argon as the first Gemini 4-generation model aimed at long-horizon software engineering, enterprise knowledge work, and cyber defense. It can generate up to 1M output tokens in a single response, up from 64K on earlier Gemini models. Output-length and safety-guardrail changes enable larger refactors and longer reports in one turn, with a phased U.S. government pre-release process and pricing starting at $2 per 1M input tokens and $10 per 1M output tokens.
Google unveiled Gemini 4 Argon, positioning it against Anthropic and OpenAI and saying it is already using the model internally. Argon’s single-response output limit rose to up to 1,000,000 tokens from 64,000, alongside a launch price of $2 per million input tokens and $10 per million output tokens. The model is being released first to selected cybersecurity experts and then to paying API customers and Google AI Ultra subscribers, with broader public access left without a set date.
Google announced Gemini 4 Argon, a new AI model aimed at complex software engineering, enterprise knowledge work, and cybersecurity defense. Access is being limited initially to a set of trusted cyber defenders, while Google works through the U.S. government’s voluntary pre-release access process. Over time, Google plans to gradually expand who can use the model.
The issue directs readers to watch a Dyna-2.1 demo video to see how physical-agent tasks play out as many small decisions and manipulations. It says the run shows what an hour of physical-agent work looks like. As a result, the focus shifts from one scripted move to the broader robotics challenge described as fitting many steps together.
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