Google announces Argon AI model

WorldTechnology
2 Oct 2026 • 12:05 AM MYT
The Manila Times
The Manila Times

One of the longest-running English broadsheets in the Philippines

Google announces Argon AI model

SAN FRANCISCO, California — Alphabet’s Google on Wednesday announced a new top-tier artificial intelligence (AI) model to anchor its Gemini 4 generation of models in a fresh bid to catch up to rivals Anthropic and OpenAI in the AI race.

The new model, “Argon,” is larger in size than Google’s previous line of advanced “Pro” models, a company spokesman said.

“It’s our most performant model yet built for complex workloads, and we see it comparable to frontier models like [OpenAI’s] Astra and [Anthropic’s] Opus on key coding and cyber benchmarks,” the spokesman said.

Google said it was providing the model to select cybersecurity partners and was participating in the Trump administration’s voluntary process for prerelease model access. It did not provide a timeline for the model’s public release.

The model posted better marks than Astra and Opus in terms of self-reported performance on several industry benchmarks, per a company press release. Still, Argon remained behind on certain other metrics, including two of the four coding-related benchmarks Google included in the release.

Google no longer plans to release Gemini 3.5 Pro, which CEO Sundar Pichai originally said would be released in June, according to the company spokesman.

In the intervening time, Google overhauled its DeepMind AI lab, with its founder and CEO Demis Hassabis stepping aside and several leaders of its Gemini model leaving the company.

The months of delays to its AI model have caused the company to fall behind Anthropic and OpenAI, which continued to push the research frontier with new releases to its top models.

Pichai in July pushed back on the notion hat Google was losing ground in the AI race. But Google in recent months has shifted its messaging from touting Gemini’s cutting-edge capabilities to highlighting its cost advantage compared to competitor models.

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