Google opened Gemini 4 Argon to everyone on 13 October, and on Google's own benchmark table it leads Claude Opus 5.5 on automation work while Opus still wins in the terminal. These are Google's numbers, Argon first and Opus 5.5 second: - AutomationBench: 51.3% against 42.5% - DeepSWE v1.1: 77.9% against 74.2% - Terminal Bench 4.0: 57.4% against 66.4% - FrontierSWE v2: 55.0% against 62.3% It is in the Gemini API through AI Studio now, at an introductory $2 per million input tokens and $10 per million output, going to $4 and $20 after 30 November. The Gemini app has it for Pro and Ultra subscribers. The first hands on reports are more mixed than the table. ariwilson on Hacker News ran his own eleven bug fixes through it and it solved ten, but a median run cost him $0.52 against $0.18 for Sonnet 5.5 and took about four minutes against 32 seconds, because it wrote around 24k output tokens where Sonnet wrote about 3k. eyalitki gave it a payroll question, watched it get every edge case right, and then saw it work out 430 minus 60 as 410. Google's own engineers left it running overnight on ADK, their 200,000 line Python agent framework, and the changes it made are now live, with in memory session prep in long sessions down 40 percent. If you build with n8n or Claude Code, I would not move anything yet. An automation step that keeps failing on a long, many step task is the cheap thing to try it on at the introductory price, and for work in the terminal Opus 5.5 still has the better number. 🔗 https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/ The tester's numbers: https://news.ycombinator.com/item?id=50077034 Which step in your own workflows would you hand to a new model first?