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Google · Text model · GA
Gemini 4 Argon
Google: our flagship reasoning model, built for complex software engineering, deep maths and science problem solving and autonomous multi-step agents ai.google.dev (opens in a new tab)
Figures checked 1 Nov 2026. A dash means not published on the sources we checked, so it stays blank rather than estimated. AA index and speed are from Artificial Analysis at the high setting.
Reasoning levels
Which level to choose
Google names these settings thinking_level. Price per token is the same at every level. Higher levels usually use more output tokens. ai.google.dev (opens in a new tab)
Google: Remote MCP in the Interactions API, Streamable HTTP servers only ai.google.dev (opens in a new tab). These official remote MCP servers fit that rule. We have not tested each server with this model. A server that publishes a client list is left out when this lab is not on it.
Google DeepMind releases Gemini Robotics 2.5 for real-world robots
DeepMind says its new vision-language-action model, built with Gemini 4 Argon, was tested on more than 200 tasks, finishes tasks 20% to 30% faster than the previous version and packed automotive parts with a 96% success rate in proof-of-concept tests at Mercedes-Benz. It is rolling out through partners including Agile Robots, Apptronik and Boston Dynamics. The figures are DeepMind's own; more robot training and inference means more GPU demand in data centres.
One robots.txt line to opt a website out of AI training
Google says it will support a shared AI training control in robots.txt, alongside Microsoft, OpenAI and Anthropic. It is based on an IETF draft. Website owners get one switch instead of one per crawler.
Google Cloud revenue more than doubles as Alphabet spends $51.4bn in a quarter
Alphabet put $51.4bn into capex in Q3, about 35% of its technical infrastructure spend going to data centres. Google Cloud revenue grew 103% to $30.7bn.
