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Google unveils Gemini 4 Argon for long-running work

Google announced its new frontier model, Gemini 4 Argon, in a dpa report timed at 02:00 on 5 October 2026.

dpa said Argon is initially rolling out to trusted cyber defenders through Google’s Fairwind Program, a limited-access initiative by Google DeepMind and Google Cloud. The company said the model is designed for complex, long-running tasks across software engineering, legal and financial work, and cybersecurity. It will initially be available to paid API customers and Google AI Ultra subscribers.

Gemini 4 Argon pricing and early internal use

Argon will launch at $2 per million input tokens and $10 per million output tokens. Cached input tokens are priced at a 95 percent discount. Google has also raised the model’s output limit to 1 million tokens from 64,000 tokens.

Google said Argon is already being used internally for coding, research and writing. dpa reported that the model helped quantum computing researchers beat a published optimization baseline by 40 percent in one case. It also identified memory improvements that could save up to 1 PiB across Google’s data centers.

Argon agents are helping migrate C and C++ code to Rust. For Google’s libgav1 video decoder, the agents replaced 32,000 lines of SIMD code. Google said the Rust version runs 2.7 times faster than the previous Rust version.

dpa also reported that Google is strengthening safeguards against misuse, prompt injection and model misalignment before broader availability. The article did not give a date for that wider release, and it did not name a general consumer rollout beyond paid API customers and Google AI Ultra subscribers.

The same report is the only source used for these figures. Prices, the token limits, the 40 percent optimization case, the data-center memory figure, the 32,000 lines of code and the 2.7-times speed claim are stated as Google’s account, as relayed by dpa, not as independently measured results.

Source: dpa international

Photo: NOIRLab/NSF/AURA/T. Slovinský / Wikimedia Commons, CC BY 4.0 (resized)

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