Google DeepMind Unveils Gemini 4 Argon with 1M Output Tokens for Coding, Knowledge Work and Cyber Defense

來源原標題

Google DeepMind Unveils Gemini 4 Argon with 1M Output Tokens for Coding, Knowledge Work and Cyber Defense

作者

Asif Razzaq

原始標籤

Agentic AI · AI Infrastructure · AI Shorts · Applications · Artificial Intelligence · Comparison · Editors Pick · Enterprise AI · For Devs · Guardrail · Harness · Language Model · Large Language Model · Machine Learning · New Releases · Software Engineering · Staff · Tech News · Technology

原始連結

https://www.marktechpost.com/2026/09/30/google-deepmind-unveils-gemini-4-argon-with-1m-output-tokens-for-coding-knowledge-work-and-cyber-defense/

摘要原文

Google DeepMind has just announced Gemini 4 Argon , its new frontier model and the first model of the Gemini 4 generation. It targets long-horizon software engineering, enterprise knowledge work in legal and finance, and cybersecurity defense. The biggest technical change is output length. Argon can generate up to 1M tokens in a single response, up from 64K on earlier Gemini models. Google DeepMind described Argon as built for complex workflows across coding, enterprise knowledge work and cybersecurity defense. Google is taking a phased approach. It is participating in the U.S. government’s voluntary process for pre-release model access. It will gather feedback from early testers and iterate on guardrails before a wider release. Pricing is already public. Argon launches at an introductory $2 per 1M input tokens and $10 per 1M output tokens. Cached input tokens get a 95% discount, which works out to $0.10 per 1M. After the introductory period, pricing moves to $4 input and $20 output. Logan Kilpatrick confirmed the introductory $2 in and $10 out pricing. Current frontier APIs cap a single response far lower. Claude Opus 5.5 , Claude Fable 5.1 and GPT-6 Astra each allow 128K output tokens. Google team states that Argon can think deeply and generate hundreds of thousands of tokens in one trajectory. For developers, that means large refactors or long reports without splitting work across turns. The cost is real, though. A full 1M output tokens costs $10 at introductory pricing and $20 after. Google has not disclosed Argon’s input context window. Google compared Argon against GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1. Argon leads outright on 12 of 18 benchmarks and ties for first on 1. Artificial Analysis reported that Argon equals GPT-6 Astra on its Intelligence Index at 60% of the cost per task, using discounted prices. Google trained Argon to autonomously find, validate and patch critical software vulnerabilities. Trusted defenders and internal Google teams receive it without cyber guardrails. On CWE-bench v1 , which tests vulnerability remediation, Argon ties for first at 68%. The rival models on that leaderboard run inside their own agent harnesses. Wiz is already using Argon through its Scan for Good initiative. The model found a critical vulnerability in healthcare software used by hospitals worldwide. Google says previous frontier models had missed it. Before broad release, Google is strengthening safeguards in 4 areas: Thousands of Googlers already use Argon. Google shared 4 internal results: Sources: Google , Anthropic Opus pricing , Anthropic Fable 5.1 docs , OpenAI GPT-6 Astra docs , OpenRouter . Benchmark scores are from Google’s published comparison. GPT-6 Astra prices are its short-context tier. Check out the technical details . All credit goes to the researcher of this project. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter . Wait! are you on telegram? now you can join us on telegram as well. Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with us The post Google DeepMind Unveils Gemini 4 Argon with 1M Output Tokens for Coding, Knowledge Work and Cyber Defense appeared first on MarkTechPost .