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Gemini 4 Argon: Google's AI That Writes a Million Tokens in One Go

Google DeepMind's Gemini 4 Argon: A Million-Token Output and a Laser Focus on Hard Problems

What if an AI could write an entire codebase, a full technical report, or a multi-step automation script in one continuous stream—no copy-paste, no breaking it into chunks? That's the promise of Gemini 4 Argon, which Google DeepMind launched on September 30.

The headline number: 1 million tokens in a single output. That's not the context window—it's how much the model can generate in one go. For comparison, most cutting-edge models cap out around 128,000 tokens. Argon's leap means deep codebase migrations, lengthy legal documents, and complex workflows can finally flow from start to finish without interruption.

Built for the Long Haul

Google isn't positioning Argon as a general-purpose chatbot. It's aimed squarely at complex, long-term workflows in software engineering, law, finance, and cybersecurity defense. The rollout is phased: first to trusted cybersecurity professionals, then developers, enterprises, and subscribers.

The early benchmark scores are impressive. On DeepSWE v1.1, a long-horizon software engineering test, Argon hit 77.9%—a record. It also topped the Vals Index (a weighted measure of finance, programming, law, and taxation) and Zapier's AutomationBench with 51.3%. For long video understanding, LVBench, it reached 91.7%, the highest yet. And it can handle professional charts, extract details from lengthy videos, and perform cross-document actions.

Security That Plays Defense

Cybersecurity is the core narrative here. Argon is trained to autonomously discover, verify, and fix critical vulnerabilities. For trusted defenders and Google's internal teams, there's even a "no network barrier" version.

Security vendor Wiz used Argon through the Scan for Good project to uncover a serious vulnerability in a global hospital's medical software—one that previous cutting-edge models had missed. On CWE-bench v1, which tests vulnerability repair, Argon ranked first with 68%.

Before a wider release, Google is reinforcing four advanced defenses: preventing abuse, blocking prompt injection, monitoring misaligned reasoning chains, and strengthening sandboxes. Thousands of Google employees are already using Argon to debug code, design algorithms, and migrate large codebases. In one case, it improved quantum algorithms by 40% in minutes.

Pricing and Availability

During the introductory period, Argon costs $2 per million input tokens and $10 per million output tokens. After that, prices will double to $4 and $20, respectively.

Key Points

  • 1 million token output: Generate entire codebases or long reports in one continuous stream.
  • Targeted at professionals: Focused on software engineering, law, finance, and cybersecurity.
  • Top benchmark scores: 77.9% on DeepSWE v1.1, 91.7% on LVBench, and first place on Vals Index and AutomationBench.
  • Security-first: Autonomously finds and fixes vulnerabilities; already caught a hospital software flaw.
  • Phased rollout: Starts with trusted cybersecurity pros, then expands.
  • Introductory pricing: $2/$10 per million tokens, later $4/$20.

Argon isn't here to chat. It's here to tackle the hardest challenges professionals face—and it's bringing a million tokens to the fight.