Google Makes Gemini 4 Argon Available to Developers, Enterprises and Consumers

Google said its Gemini 4 Argon model is now available worldwide. "We're giving developers, enterprises, scientists, and consumers access to our latest frontier model," said Koray Kavukcuoglu, SVP of Google DeepMind and Chief AI Architect at Google.

Availability and pricing

Google said developers and enterprises can access Argon through the API in AI Studio and the Gemini platform. Google AI Ultra subscribers can use the model in Google Antigravity, and Google AI Ultra and Pro subscribers can access it in the Gemini app and in AI Mode in Search.

Google set an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens discounted 95%.

Performance claims

Google said Argon is built for sustained, multi-step work across domains including coding, finance, legal, cybersecurity and science. The company said Argon outperforms other frontier models on benchmarks across these domains and ranks first on the Vals Index, which Google described as a measure of model performance across economic sectors such as finance, coding, legal and tax work.

Internal and external use cases

Google said teams at the company, along with enterprises and researchers, have already used Argon on a range of projects.

In Chrome, Google said Argon helped engineers separate core webpage-handling code from a roughly 6 million-line legacy folder inside Chromium's 40 million-line codebase, completing an architectural refactor across hundreds of files that the company said would normally take months in a matter of weeks. Google said the change will let live webpages move between tabs, side panels and floating windows without reloading, which it said eliminates an entire category of browser crashes.

Google said that across its own engineering teams, using Argon inside Antigravity increased agentic code submissions by more than 35% while cutting code rollbacks by nearly a third.

On the open-source Agent Development Kit, Google said engineers gave Argon a rulebook and a one-paragraph goal to reduce framework overhead without breaking existing applications. Working overnight, Google said the model produced changes, now live in the google/adk-python repository, that cut in-memory session prep time by 40% in long sessions and sped up cold imports by 21%.

Google said it used Argon to speed up xTB, an open-source quantum chemistry package, making it up to 2.3 times faster at predicting molecular structures and 1.8 times faster at conformer search, with the changes contributed to the project's official GitHub repository.

The company also said Argon helped achieve a 2.85x end-to-end inference speedup for its open Gemma models on an A100 GPU using vLLM, raising throughput on Gemma 4 E2B from about 37,900 to more than 108,000 tokens per second. Google said this was done in a few days with full token parity and no quality loss, compared with a process it said would usually take months.

Google additionally said Argon shows improvements in spatial reasoning, mathematical precision and visual coding compared with earlier Gemini models, and that Google employees have used it inside Antigravity to prototype 3D visualizations, games and interactive animations.

Source: Google, "Gemini 4 Argon: Built to solve your hardest problems," published Oct. 13, 2026.