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  • MARCH 3, 2026 / Gemini

    How we built the Google I/O 2026 Save the Date experience

    Google I/O 2026 is returning May 19-20 at Shoreline Amphitheatre in Mountain View, CA. But before the keynotes begin, you can get into the spirit of the event with our annual tradition: the save the date puzzle. This year's experience highlights how AI can empower and accelerate

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  • FEB. 19, 2026 / Gemini

    Turn creative prompts into interactive XR experiences with Gemini

    The Android XR team is using Gemini's Canvas feature to make creating immersive extended reality (XR) experiences more accessible. This allows developers to rapidly prototype interactive 3D environments and models on a Samsung Galaxy XR headset using simple creative prompts.

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  • FEB. 17, 2026 / Gemini

    Get ready for Google I/O 2026

    Google I/O returns May 19-20. Watch the livestreams for updates on Android, AI, Chrome, and Cloud. Registration is open on the Google I/O website.

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  • SEPT. 4, 2025 / Gemma

    Introducing EmbeddingGemma: The Best-in-Class Open Model for On-Device Embeddings

    Introducing EmbeddingGemma: a new embedding model designed for efficient on-device AI applications from Google. This open model is the highest-ranking text-only multilingual embedding model under 500M parameters on the MTEB benchmark, enabling powerful features like RAG and semantic search directly on mobile devices without an internet connection.

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  • AUG. 27, 2025 / Gemini

    Beyond the terminal: Gemini CLI comes to Zed

    Google and Zed have partnered to integrate Gemini CLI directly into the Zed code editor, bringing AI capabilities directly into the editor for developers and allowing for faster and more focused coding, enabling tasks like in-place code generation, instant answers, and natural chat within the terminal with a seamless review workflow for AI-generated changes.

    Gemini CLI is now integrated into Zed, bringing AI directly to your code editor
  • AUG. 26, 2025 / Gemini

    Introducing Gemini 2.5 Flash Image, our state-of-the-art image model

    Gemini 2.5 Flash Image is a new state-of-the-art image generation and editing model that allows for blending multiple images, maintaining character consistency, and targeted transformations using natural language, leveraging Gemini's world knowledge, now available through the Gemini API, Google AI Studio, and Vertex AI.

    Introducing Gemini 2.5 Flash Image
  • AUG. 21, 2025 / Gemini

    What's new in Gemini Code Assist

    Gemini Code Assist's Agent Mode, now available in VS Code (Preview) and IntelliJ (Stable), streamlines complex coding tasks by proposing detailed plans for user review and approval. This intelligent, collaborative approach, enhanced with features like inline diffs and persistent chat history, aims to boost developer productivity and efficiency.

    New in Gemini Code Assist: Agent Mode more widely available, IDE improvements and Gemini CLI updates
  • AUG. 18, 2025 / Gemini

    URL context tool for Gemini API now generally available

    The Gemini API's URL Context tool is now generally available, allowing developers to ground prompts using web content instead of manual uploads. This release expands support to PDFs and images.

    URL context tool for Gemini API now generally available
  • AUG. 15, 2025 / Google AI Studio

    Announcing Imagen 4 Fast and the general availability of the Imagen 4 family in the Gemini API

    Google announces the general availability of Imagen 4, its advanced text-to-image model, in the Gemini API and Google AI Studio, featuring significant improvements in text rendering. The new Imagen 4 Fast model, designed for speed and rapid image generation, is now available alongside Imagen 4 and Imagen 4 Ultra, with Imagen 4 and Imagen 4 Ultra also supporting up to 2K resolution image generation.

    Imagen 4 Fast and the generally availability of the Imagen 4 family in the Gemini API
  • AUG. 14, 2025 / Gemma

    Introducing Gemma 3 270M: The compact model for hyper-efficient AI

    Google's new Gemma 3 270M is a compact, 270-million parameter model offering energy efficiency, production-ready quantization, and strong instruction-following, making it a powerful solution for task-specific fine-tuning in on-device and research settings.

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