Skip to main content

Gemini 4 Argon: 1M Token Output, Built for the Long Haul

Google DeepMind's Gemini 4 Argon: A Million Tokens, No Breaks

Google DeepMind quietly dropped its latest model, Gemini 4 Argon, on September 30. The headline? It can generate a staggering 1 million tokens in a single output—that's not the context window, but the length of what it can produce in one go. For context, most cutting-edge models max out around 128,000 tokens. Argon's leap means you can ask it to write a massive codebase migration or a long technical report without breaking it into chunks. The result? Seamless continuity from start to finish.

Image

Built for the Long Run

Argon isn't your average chatbot. Google is positioning it for "complex, long-term workflows"—think software engineering, law, finance, and cybersecurity defense. And the benchmarks back it up: DeepSWE v1.1, a long-horizon software engineering test, hit a record 77.9%. Vals Index, which weighs finance, programming, law, and taxation, ranked it first. Zapier's AutomationBench gave it a 51.3% score, also top. And for long video understanding, LVBench, it reached 91.7%, the highest yet. On the visual side, it can handle professional charts, pull details from lengthy videos, and perform cross-document actions.

Security That Goes on the Offense

Cybersecurity is the core narrative here. Argon is trained to autonomously find, verify, and fix critical vulnerabilities. For trusted defenders and Google's internal teams, there's even a "no network barrier" version. In one case, security vendor Wiz used it through the Scan for Good project to spot a serious flaw in a global hospital's medical software—something previous cutting-edge models had missed. On the CWE-bench v1 vulnerability repair benchmark, it ranked first with 68%.

Pricing and Access: A Phased Rollout

Don't expect to sign up and start using Argon tomorrow. Google is rolling it out in phases: first to trusted cybersecurity professionals, then to developers, enterprises, and subscription users. Pricing comes in two tiers: during the introductory period, it's $2 per million input tokens and $10 per million output tokens; later, that jumps to $4 and $20. Before wide release, Google is beefing up 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 handle large-scale code migrations. In one case, quantum algorithms were improved by 40% in minutes. Clearly, Argon isn't built for casual chat—it's for tackling the hardest challenges professionals face.

Key Points:

  • Gemini 4 Argon outputs up to 1 million tokens in one go, far beyond the typical 128K limit.
  • Targets complex, long-term workflows in software engineering, law, finance, and cybersecurity.
  • Tops benchmarks like DeepSWE v1.1 (77.9%), Vals Index, AutomationBench (51.3%), and LVBench (91.7%).
  • Focuses on cybersecurity defense, autonomously finding and fixing vulnerabilities.
  • Phased rollout: first to security pros, then developers and enterprises; pricing starts at $2/$10 per million tokens.