Gemini 2.5 Flash Image Integrations

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

Google AI Studio is an all-in-one environment designed for building AI-first applications with Google’s latest models. It supports Gemini, Imagen, Veo, and Gemma, allowing developers to experiment across multiple modalities in one place. The platform emphasizes vibe coding, enabling users to describe what they want and let AI handle the technical heavy lifting. Developers can generate complete, production-ready apps using natural language instructions. One-click deployment makes it easy to move from prototype to live application. Google AI Studio includes a centralized dashboard for API keys, billing, and usage tracking. Detailed logs and rate-limit insights help teams operate efficiently. SDK support for Python, Node.js, and REST APIs ensures flexibility. Quickstart guides reduce onboarding time to minutes. Overall, Google AI Studio blends experimentation, vibe coding, and scalable production into a single workflow.

OpenRouter serves as a consolidated interface for various large language models (LLMs). It efficiently identifies the most competitive prices and optimal latencies/throughputs from numerous providers, allowing users to establish their own priorities for these factors. There’s no need to modify your existing code when switching between different models or providers, making the process seamless. Users also have the option to select and finance their own models. Instead of relying solely on flawed evaluations, OpenRouter enables the comparison of models based on their actual usage across various applications. You can engage with multiple models simultaneously in a chatroom setting. The payment for model usage can be managed by users, developers, or a combination of both, and the availability of models may fluctuate. Additionally, you can access information about models, pricing, and limitations through an API. OpenRouter intelligently directs requests to the most suitable providers for your chosen model, in line with your specified preferences. By default, it distributes requests evenly among the leading providers to ensure maximum uptime; however, you have the flexibility to tailor this process by adjusting the provider object within the request body. Prioritizing providers that have maintained a stable performance without significant outages in the past 10 seconds is also a key feature. Ultimately, OpenRouter simplifies the process of working with multiple LLMs, making it a valuable tool for developers and users alike.

GitHub stands as the leading platform for developers globally, renowned for its security, scalability, and community appreciation. By joining the ranks of millions of developers and businesses, you can contribute to the software that drives the world forward. Collaborate within the most inventive communities, all while utilizing our top-tier tools, support, and services. If you're overseeing various contributors, take advantage of our free GitHub Team for Open Source option. Additionally, GitHub Sponsors is available to assist in financing your projects. We're thrilled to announce the return of The Pack, where we’ve teamed up to provide students and educators with complimentary access to premier developer tools throughout the academic year and beyond. Furthermore, if you work for a recognized nonprofit, association, or a 501(c)(3), we offer a discounted Organization account to support your mission. With these offerings, GitHub continues to empower diverse users in their software development journeys.

Gemini is Google’s intelligent AI platform built to support productivity, creativity, and learning across work, school, and everyday life. It allows users to ask questions, generate text, images, and videos, and explore ideas using conversational AI powered by Gemini 3. By integrating directly with Google Search, Gemini provides grounded answers and supports detailed follow-up discussions on complex topics. The platform includes advanced tools like Deep Research, which condenses hours of online research into structured reports in minutes. Gemini also enables real-time collaboration and spoken brainstorming through Gemini Live. Users can connect Gemini to Gmail, Google Docs, Calendar, Maps, and other Google services to complete tasks across multiple apps at once. Custom AI experts called Gems allow users to save instructions and tailor Gemini for specific roles or workflows. Gemini supports large file analysis with a long context window, making it capable of reviewing books, reports, and large codebases. Flexible subscription tiers offer different levels of access to models, credits, and creative tools. Gemini is available on web and mobile, making it accessible wherever users need intelligent assistance.

Gemini Enterprise, an all-encompassing AI platform from Google Cloud, is designed to harness the full capabilities of Google’s sophisticated AI models, tools for creating agents, and enterprise-level access to data, seamlessly integrating these into daily workflows. This innovative solution features a cohesive chat interface that facilitates employee interaction with internal documents, applications, various data sources, and personalized AI agents. The foundation of Gemini Enterprise consists of six essential elements: the Gemini suite of large multimodal models, an agent orchestration workbench (previously known as Google Agentspace), ready-made starter agents, powerful data integration connectors for business systems, extensive security and governance frameworks, and a collaborative partner ecosystem for customized integrations. Built to scale across various departments and organizations, it empowers users to develop no-code or low-code agents capable of automating diverse tasks like research synthesis, customer service responses, code assistance, and contract analysis while adhering to corporate compliance regulations. Moreover, the platform is designed to enhance productivity and foster innovation within businesses, ensuring that users can leverage advanced AI technologies with ease.

Fal represents a serverless Python environment enabling effortless cloud scaling of your code without the need for infrastructure management. It allows developers to create real-time AI applications with incredibly fast inference times, typically around 120 milliseconds. Explore a variety of pre-built models that offer straightforward API endpoints, making it easy to launch your own AI-driven applications. You can also deploy custom model endpoints, allowing for precise control over factors such as idle timeout, maximum concurrency, and automatic scaling. Utilize widely-used models like Stable Diffusion and Background Removal through accessible APIs, all kept warm at no cost to you—meaning you won’t have to worry about the expense of cold starts. Engage in conversations about our product and contribute to the evolution of AI technology. The platform can automatically expand to utilize hundreds of GPUs and retract back to zero when not in use, ensuring you only pay for compute resources when your code is actively running. To get started with fal, simply import it into any Python project and wrap your existing functions with its convenient decorator, streamlining the development process for AI applications. This flexibility makes fal an excellent choice for both novice and experienced developers looking to harness the power of AI.

Nano Banana offers a streamlined, user-friendly way to generate and edit images using Gemini’s “Fast” model. It focuses on fun, casual transformations, making it great for remixing selfies, trying new styles, or merging multiple pictures into a single creation. The model handles character consistency well, ensuring that people look like themselves even when placed in new settings or artistic interpretations. Users can easily perform spot edits like changing backgrounds, adjusting small details, or adding creative elements without needing advanced controls. Nano Banana also excels at playful results such as figurine effects, retro photo booth aesthetics, or themed portraits. These quick edits allow anyone to explore creative concepts in seconds. It’s built for low-effort, high-fun experimentation, making it perfect for social media content or personal projects. Nano Banana provides an approachable entry point for image generation without the depth or complexity of Pro-level features.

We are excited to announce the beta launch of SynthID, a groundbreaking tool designed for the watermarking and identification of AI-generated images. Currently, SynthID is being made available to a select group of Vertex AI customers utilizing Imagen, which is among our newest text-to-image models that transform textual input into stunning photorealistic visuals. This innovative tool allows users to seamlessly embed an invisible digital watermark within their AI-generated images, enabling them to ascertain whether Imagen was involved in the creation of the image or even specific elements of it. The ability to recognize AI-generated content is essential for fostering trust in the information landscape. Although it is not a definitive solution to the complexities of misinformation, SynthID represents an early and encouraging technical advancement in tackling this urgent issue surrounding AI safety. Developed by Google DeepMind and honed through collaboration with Google Research, this technology holds the potential for adaptation across various AI models, and we are committed to integrating it into additional products in the coming months. As the landscape of AI continues to evolve, SynthID aims to play a crucial role in ensuring transparency and accountability in digital content.