Google releases three new AI models

Google unveiled three new AI models, led by its most powerful Gemini 3.6 Flash. Photo / Getty Images

Google on Tuesday released three new artificial intelligence models, including Gemini 3.6 Flash, its most powerful, and Gemini 3.5 Flash Cyber, which is fine-tuned for cyber security.

Google is aiming to compete with rivals such as Anthropic and OpenAI on cutting-edge models and on cyber security, an area in which the two startups have forged ahead this year with powerful systems that can identify security vulnerabilities in software.

Gemini Flash 3.6 improves on the capabilities of Google’s previous version of Flash, which performed strongly on benchmarks like coding and finance tasks, according to AI leaderboards. The new model is also cheaper for users.

Gemini 3.5 Flash Cyber can find and patch security vulnerabilities at a lower cost than other larger models, the company said. The third model, Gemini 3.5 Flash-Lite, is designed for tasks like managing AI “agents”, which are bots that can act autonomously to function like digital personal assistants.

Google has also been working on a flagship AI model called Gemini 3.5 Pro, which is expected to be its highest-performing system. The Silicon Valley company had said in May that Pro would be rolled out in June, but it remains unavailable. Google said Pro was still in testing and would be made “broadly available as soon as it’s ready”.

Since OpenAI’s ChatGPT chatbot kicked off the AI boom in 2022, Google has poured money and effort into leading the race.

But in recent months, Google has been upstaged by advanced new models from Anthropic and OpenAI as well as new models from Chinese startups such as Moonshot AI. This month, Meta, the owner of Facebook and Instagram, also released a model that crept ahead of Gemini’s capabilities, according to several leaderboards.

Google said the new Flash models would be available for a lower cost than its previous offerings. The systems use 17% fewer tokens, which are the units of measurement for AI use, than earlier models. That means developers will spend less money to complete the same tasks.

This article originally appeared in The New York Times.

Written by: Kate Conger