AI
Gemini 3 Flash in Gemini CLI: Faster Agentic Coding for Terminal Workflows at a Lower Cost
Credit: Google
Gemini 3 Flash in Gemini CLI is now rolling out to help developers move faster in the terminal without sacrificing code quality. Terminal-based work tends to be high-frequency: quick fixes, rapid iterations, and lots of small decisions that add up. Gemini 3 Flash is designed for that pace, combining speed and efficiency while still delivering strong agentic coding performance.
Gemini 3 Flash in Gemini CLI: What’s new for developers
Gemini 3 Flash achieves a reported 78% SWE-bench Verified score for agentic coding, outperforming the 2.5 series and even Gemini 3 Pro on that specific benchmark. It’s also available in preview at less than a quarter of the cost of Gemini 3 Pro. In practical terms, Gemini 3 Flash in Gemini CLI targets the sweet spot where you want reliable reasoning and clean edits, but you also want results quickly and at a lower token cost.
Most paid-tier customers can access both Gemini 3 Pro and Gemini 3 Flash, including non-business Google AI Pro or AI Ultra users, developers using a paid API key through Google AI or Vertex, and Gemini Code Assist users enabled for preview models by their cloud admin. Free-tier access is expanding as well, with the earlier waitlist already onboarded and broader availability rolling out gradually.
To start using Gemini 3 Flash in Gemini CLI, update to version 0.21.1 or later using: npm install -g @google/gemini-cli@latest
Then open /settings, toggle Preview features to true, and use /model to select Gemini 3.
Gemini 3 Flash in Gemini CLI is especially useful when you’re scanning long pull request threads for one actionable request, applying precise config tweaks, or generating scripts for load testing and quickly patching them when errors appear. With auto-routing available, you can still reserve Pro for the hardest reasoning while using Flash for the bulk of everyday terminal work.
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Google Translate Live Translate update is rolling out with a refreshed interface and improved audio customization features, making real-time language conversations more intuitive and user-friendly. According to a recent report by Android Authority, Google is testing notable enhancements that refine how users interact with Live Translate inside Google Translate.
Refreshed Interface for Better Conversations
The updated Live Translate interface focuses on clarity and ease of use. The redesign simplifies on-screen elements, making conversations between two languages feel more seamless. Buttons are better positioned, text is more readable, and the layout appears cleaner compared to previous versions.
Live Translate, also known as Conversation Mode, allows two people speaking different languages to communicate in real time. With this update, starting and managing multilingual conversations becomes quicker and less cluttered. The improved layout is particularly useful for travelers, business professionals, and students who rely on instant translation during discussions.
Customizable Audio Playback and Widgets
Another key improvement in the Google Translate Live Translate update is enhanced audio playback control. Users may get more flexibility in adjusting tone or playback behavior, ensuring translated speech sounds clearer and more natural in conversations.
Additionally, Google appears to be working on improved home screen widgets. These widgets allow faster access to Live Translate directly from the Android home screen. Instead of navigating through the app, users can instantly launch conversation mode with a single tap, saving valuable time.
What This Means for Android Users
The Google Translate Live Translate update signals Google’s continued investment in AI-powered communication tools. By refining the interface and adding practical customization options, the app strengthens its position as one of the most reliable real-time translation solutions on Android.
Although the features are currently spotted in testing, they suggest that a broader rollout may follow soon. If implemented widely, these changes could significantly enhance how users communicate across languages in everyday scenarios.
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Google Photos Android sticker feature is changing the way users create and share stickers directly from their photo library.
Google has quietly introduced a new tool inside Google Photos for Android that allows users to turn people, pets, or objects from their images into custom stickers. The feature eliminates the need for third-party apps and makes sticker creation faster and more convenient.
What Is the Google Photos Android Sticker Feature?
The new sticker feature uses Google’s advanced subject detection technology to identify the main element in a photo. Users simply open an image in Google Photos, long-press on the subject they want to extract, and the app automatically creates a cut-out sticker. This sticker can then be copied and shared across messaging platforms like WhatsApp and other supported apps.
Unlike traditional sticker apps that require manual background removal, this tool works seamlessly within the Google Photos ecosystem. The result is clean subject isolation with minimal effort.
How to Use the Feature
To use the Google Photos sticker tool on Android:
- Open the Google Photos app.
- Select the image from which you want to create a sticker.
- Long-press on the subject.
- Tap copy or share once the sticker preview appears.
- Paste it into a messaging or social media app.
The feature is currently rolling out to Android users and may require the latest version of Google Photos.
Why This Update Matters
Custom stickers have become an essential part of digital communication. By integrating sticker creation directly into Google Photos, Google simplifies content sharing and enhances user engagement. It also strengthens Google Photos’ position as more than just a cloud storage solution.
As visual communication continues to grow, features like this highlight how AI-powered tools are reshaping everyday smartphone usage.
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Nano Banana 2 Introduces Advanced AI Image Generation
Nano Banana 2 marks Google’s latest breakthrough in AI-powered image generation, delivering sharper visuals, improved instruction accuracy, and greater creative control for users. Designed to push the boundaries of generative AI, this upgraded model focuses on producing highly detailed, realistic images while maintaining consistency across prompts.
Google’s continued investment in artificial intelligence innovation is evident in Nano Banana 2, which builds on earlier image models with enhanced performance, better contextual understanding, and higher-resolution output capabilities. The model aims to serve creators, developers, designers, and enterprises seeking scalable AI-generated visuals.\
Enhanced Image Quality and Precision
One of the most notable improvements in Nano Banana 2 is its ability to generate high-resolution images with refined detail. The system demonstrates improved subject consistency, ensuring that characters, objects, and environments remain accurate across variations. This is particularly valuable for branding, storytelling, and commercial design applications.
Additionally, Nano Banana 2 offers better adherence to user instructions. Whether generating photorealistic landscapes, product mockups, or stylized illustrations, the model interprets prompts with greater precision. This reduces the need for repeated refinements and increases productivity for creative professionals.
Integration Across Google’s AI Ecosystem
Nano Banana 2 is positioned as part of Google’s broader AI ecosystem, integrating with tools and platforms that empower users to create, edit, and experiment seamlessly. By embedding advanced generative capabilities into widely used services, Google aims to make AI image generation more accessible and practical for everyday workflows.
The model also emphasizes responsible AI development, aligning with Google’s approach to safety, transparency, and reliability. As AI-generated content becomes more mainstream, maintaining quality and trust remains a key priority.
Why Nano Banana 2 Matters
The launch of Nano Banana 2 signals a major step forward in AI image technology. With improved realism, advanced prompt understanding, and ecosystem-wide integration, the model is set to redefine how individuals and businesses create digital content. As generative AI continues to evolve, Nano Banana 2 strengthens Google’s position in the competitive AI landscape while expanding creative possibilities for users worldwide.
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