Release notes
Official updates from Anthropic, OpenAI, Google, xAI, Mistral, DeepSeek and Meta, newest first. Open any update for a short AI summary and the full notes.
Google · Gemini API
Released gemini-2.0-flash-001, a generally available (GA) version of Gemini 2.0 Flash that supports text-only output. Released gemini-2.0-pro-exp-02-05, an experimental public preview version of Gemini 2.0 Pro. Released gemini-2.0-flash-lite-preview-02-05, an experimental public preview model optimized for cost efficiency. Added file input and graph output support to code execution. Released the Google Gen AI SDK for Python to general availability (GA).
Google · Gemini app
What: Starting today, Gemini app users have access to our 2.0 Flash Thinking Experimental model. Built on the speed and performance of 2.0 Flash, this model is trained to break down prompts into a series of steps to strengthen its reasoning capabilities and deliver better responses. 2.0 Flash Thinking Experimental shows its thought process to users so you can see why it responded in a certain way, what its assumptions were, and trace the model's line of reasoning. Users can also try 2.0 Flash Thinking Experimental with apps, our thinking model designed to give you access to agentic capabilities through the use of connected apps such as YouTube, Maps, and Search for complex multi-step questions. These connected apps already make the Gemini app a uniquely helpful AI-powered assistant, and we’re exploring how new reasoning capabilities can combine with your apps to help you do even more. Both 2.0 Flash Thinking Experimental models are now rolling out to the Gemini web and mobile app. We’ll expand access to enterprise accounts in the coming weeks These experimental models are meant to be an early preview and may make mistakes. Additionally these models won't be compatible with some Gemini features in their experimental state. Why: We believe in rapid iteration and bringing the best of Gemini to the world. Your feedback helps us improve these models over time and learning from experimental launches informs how we release models more widely.