Last week we announced that Gemini Enterprise has evolved to make it even simpler to get work done, and introduced the Gemini agent , your new universal agent for work. It's always on and ready to answer your questions. It will write code, complete longer and more complex tasks, or perform whatever you need to get the job done, all from a single prompt box. And model intelligence underpins it all. To enable a new frontier of work, we are making our new frontier model, Gemini 4 Argon , available on Google Cloud.
We trained Argon to work with both depth and precision, which allows it to maintain context across long, multi-step tasks which are reinforced with strong domain expertise along the way. Whether your team is running complex software builds, handling detailed financial and legal work, or deploying cybersecurity tools like CodeMender , Argon helps your teams maintain focus from start to finish. Your teams already use Gemini for business to answer questions and draft content. With Argon, they can hand off the deep, multi-step work that used to take hours or days, and get back finished work they can use.
Argon reads long documents that mix text, tables, charts and images, and turns them into one clear output grounded in those sources. It can pull findings from many sources into a single structured answer, analyze data over time, and write stronger legal, finance, and executive documents. On long tasks, it keeps going until the job is done. We trained Argon to respect system boundaries, report negative findings honestly, and pause for confirmation before taking irreversible steps, and it tells you when it couldn't find something or finish a task.
Customers who tested Argon tell us it excels at turning huge, unstructured inputs into cohesive outputs. "As software development becomes more agentic, teams need models that can support long-running, multi-step work across all stages of the development lifecycle. Gemini 4 Argon is designed to help organizations bring AI into development, security, and operations while keeping it within established enterprise workflows and controls. ” – Stuart Moncada, VP, GitLab. In finance, legal, tax, and other regulated work, calculations and data extraction need to be precise, repeatable, and verifiable.