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Announced September 30, 2026. Limited rollout to selected trusted defenders through Fairwind and early testers; broader access is planned to start with paid API and Google AI Ultra users. Google states up to 1 million output tokens. A public API model ID, full rollout date and finalized API context specification are not confirmed in the reviewed sources.
Announced September 30, 2026. Limited rollout to selected trusted defenders through Fairwind and early testers; broader access is planned to start with paid API and Google AI Ultra users. Google states up to 1 million output tokens. A public API model ID, full rollout date and finalized API context specification are not confirmed in the reviewed sources.
We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
Gemini 3.5 is built to help you execute complex, agentic workflows.
Our newest audio model introduces granular audio tags that give you precise control to direct AI speech for expressive audio generation.
Gemini Robotics ER 1.6: Enhancing spatial reasoning and multi-view understanding for autonomous robotics.
Our latest voice model has improved precision and lower latency to make voice interactions more fluid, natural and precise.
Introducing Lyria 3 Pro, which unlocks longer tracks with structural awareness. We’re also bringing Lyria to more Google products and surfaces.
We’re introducing a framework to measure progress toward AGI, and launching a Kaggle hackathon to build the relevant evaluations.
Gemini 3.1 Flash-Lite is our fastest and most cost-efficient Gemini 3 series model yet.
3.1 Pro is designed for tasks where a simple answer isn’t enough.
A multijoint contact dynamics engine maintained by Google DeepMind, providing model description, physics stepping, an interactive viewer, and a Python interface. It is suitable for developing robotics, control, and reinforcement learning environments.
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
