Google AI Studio Integrations

Lua is an efficient and lightweight scripting language that is renowned for its power and versatility. It accommodates various programming paradigms, including procedural, object-oriented, functional, and data-driven programming as well as data description. With its straightforward procedural syntax and robust data description features built on associative arrays and extensible semantics, Lua stands out among scripting languages. The language is dynamically typed and operates by interpreting bytecode through a register-based virtual machine, featuring automatic memory management through incremental garbage collection, which enhances its suitability for tasks like configuration, scripting, and rapid prototyping. Lua is widely recognized for its exceptional performance, with many other scripting languages aspiring to achieve speeds comparable to Lua's. Numerous benchmarks consistently indicate that Lua ranks as the fastest among interpreted scripting languages. This impressive speed is evident not only in optimized benchmark tests but also in practical applications, where many large-scale projects have incorporated substantial portions of Lua code. The language’s efficiency and flexibility make it a popular choice among developers seeking to create high-performance applications.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Gemma 3, launched by Google, represents a cutting-edge AI model constructed upon the Gemini 2.0 framework, aimed at delivering superior efficiency and adaptability. This innovative model can operate seamlessly on a single GPU or TPU, which opens up opportunities for a diverse group of developers and researchers. Focusing on enhancing natural language comprehension, generation, and other AI-related functions, Gemma 3 is designed to elevate the capabilities of AI systems. With its scalable and robust features, Gemma 3 aspires to propel the evolution of AI applications in numerous sectors and scenarios, potentially transforming the landscape of technology as we know it.

CodeNext.ai is an innovative AI-driven coding assistant tailored for Xcode developers, featuring advanced context-aware code completion alongside interactive chat capabilities. It is compatible with numerous top-tier AI models, such as OpenAI, Azure OpenAI, Google AI, Mistral, Anthropic, Deepseek, Ollama, and others, allowing developers the convenience to select and switch models according to their preferences. The tool offers smart, instant code suggestions as you type, significantly boosting productivity and coding effectiveness. Additionally, its chat functionality empowers developers to communicate in natural language for tasks like writing code, debugging, refactoring, and executing various coding operations within or outside the codebase. CodeNext.ai also incorporates custom chat plugins, facilitating the execution of terminal commands and shortcuts right within the chat interface, thereby optimizing the overall development process. Ultimately, this sophisticated assistant not only simplifies coding tasks but also enhances collaboration and streamlines the workflow for developers.

LLM Gateway is a completely open-source, unified API gateway designed to efficiently route, manage, and analyze requests directed to various large language model providers such as OpenAI, Anthropic, and Gemini Enterprise Agent Platform, all through a single, OpenAI-compatible endpoint. It supports multiple providers, facilitating effortless migration and integration, while its dynamic model orchestration directs each request to the most suitable engine, providing a streamlined experience. Additionally, it includes robust usage analytics that allow users to monitor requests, token usage, response times, and costs in real-time, ensuring transparency and control. The platform features built-in performance monitoring tools that facilitate the comparison of models based on accuracy and cost-effectiveness, while secure key management consolidates API credentials under a role-based access framework. Users have the flexibility to deploy LLM Gateway on their own infrastructure under the MIT license or utilize the hosted service as a progressive web app, with easy integration that requires only a change to the API base URL, ensuring that existing code in any programming language or framework, such as cURL, Python, TypeScript, or Go, remains functional without any alterations. Overall, LLM Gateway empowers developers with a versatile and efficient tool for leveraging various AI models while maintaining control over their usage and expenses.

Klyra AI serves as a comprehensive suite for AI-driven content creation, offering more than 30 innovative tools designed to produce eye-catching videos, engaging social media posts, realistic product visuals, animated avatars, authentic voiceovers, original music compositions, and extensive written content like blogs and scripts, all accessible through a sleek, unified interface. Users can effectively craft and plan video stories, utilize various effects and transitions, improve or modify images, create unique musical pieces, and implement realistic text-to-speech features in diverse languages. Additionally, a collection of ready-made templates and AI-enhanced workflows simplifies the processes of brainstorming, production, and teamwork, while web-based access and API integrations allow for effortless incorporation into current marketing, educational, or design frameworks without the risk of vendor lock-in. The platform also boasts capabilities for real-time content adjustments, analytics dashboards for project tracking, and collaborative environments, which not only speed up creative processes but also enhance audience interaction by automating mundane tasks, thereby enriching the overall creative experience. The versatility and efficiency of Klyra AI make it an invaluable resource for creators looking to elevate their work.

Gemini Computer Use is an agentic computer interaction capability built into Gemini 3.5 Flash. It enables developers and enterprises to create AI agents that can work across browser, desktop, and mobile environments by seeing interfaces, reasoning through tasks, and taking action. The capability was previously offered through a standalone Gemini 2.5 computer use model, but is now natively integrated into Gemini 3.5 Flash. This gives developers access to stronger performance for agentic computer use tasks while also combining with Gemini’s existing strengths in function calling, Search grounding, Maps grounding, and built-in tools. Gemini Computer Use is designed for long-horizon automation, continuous software testing, enterprise knowledge work, and workflows that span multiple professional applications. Developers can start building with the feature through the Gemini API or Gemini Enterprise Agent Platform. Google also provides a demo environment through Browserbase for testing the capability. Safety controls include targeted adversarial training for live-environment risks, optional explicit user confirmation for sensitive or irreversible actions, and automatic task stopping when indirect prompt injection is identified. Gemini Computer Use helps organizations build practical AI agents that can complete complex digital tasks while supporting sandboxing, human review, and strict access controls.

Gemini Enterprise app is a comprehensive agentic AI platform designed to improve productivity and collaboration across organizations. It enables users to connect various workplace tools and data sources, providing a unified environment for searching, analyzing, and generating content. The platform supports multi-step automation through AI agents that can perform tasks across different applications without manual intervention. Users can leverage prebuilt Google agents or create custom agents using a no-code interface, making AI accessible to both technical and non-technical teams. Gemini Enterprise app also offers centralized control over data access, permissions, and workflows, ensuring secure and compliant operations. It is suitable for various departments, including marketing, sales, engineering, HR, and finance. By grounding AI outputs in enterprise data, it delivers more accurate and relevant results. Overall, it helps organizations operate more efficiently and make data-driven decisions.

Complete serves as a collaborative workspace powered by AI, fostering teamwork between human users and AI agents within a cohesive environment that streamlines workflows from the initial planning phase through to final delivery. By consolidating discussions, documents, and results into a singular, clear reference point, it ensures that teams can maintain a shared understanding while AI agents tackle various tasks such as debugging, documentation, code testing, and the creation of business deliverables. The platform also features organized execution threads that enable agents to carry out task-oriented projects, with teams able to observe progress and refine real outputs in real-time. Furthermore, Complete allows for the simultaneous operation of multiple AI models, facilitating the incorporation of specialized agents dedicated to coding, testing, and reasoning within the same workflow. Additionally, it seamlessly integrates with project management and development tools, bringing AI capabilities directly into the Integrated Development Environment (IDE) to enhance both coding efficiency and collaborative efforts. Moreover, this innovative workspace increasingly empowers teams to harness the full potential of AI, driving productivity and creativity in the process.

Gemini Embedding models, which include the advanced Gemini Embedding 2, are integral to Google's Gemini AI framework and are specifically created to translate text, phrases, sentences, and code into numerical vector forms that encapsulate their semantic significance. In contrast to generative models that create new content, these embedding models convert input into dense vectors that mathematically represent meaning, facilitating the comparison and analysis of information based on conceptual relationships instead of precise wording. This functionality allows for various applications, including semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation processes. Additionally, the model accommodates input in over 100 languages and can handle requests of up to 2048 tokens, enabling it to effectively embed longer texts or code while preserving a deep contextual understanding. Ultimately, the versatility and capability of the Gemini Embedding models play a crucial role in enhancing the efficacy of AI-driven tasks across diverse fields.

IvaBot serves as an AI-driven SEO solution tailored for small businesses and content creators, adept at identifying and rectifying SEO pitfalls, uncovering niche keywords, and generating engaging content that appeals to readers, ranks well on Google, and is referenced by AI tools. This versatile tool can integrate seamlessly with platforms such as WordPress, Shopify, Webflow, Wix, Squarespace, or any custom-built website without the need for plugins, setup, or coding expertise. By simply inputting a URL, users can initiate a comprehensive SEO audit that meticulously examines the website, identifies both technical and content-related issues, showcases strengths, pinpoints areas for enhancement, and prioritizes actionable fixes. Additionally, it evaluates content coverage and preparedness for AI integration by analyzing keyword employment, trust indicators, and gaps in coverage, which aids in improving Google rankings and enhances the likelihood of citation by AI systems like ChatGPT, Perplexity, Claude, and Google AI. Furthermore, IvaBot's Content Builder generates SEO briefs that leverage actual SERP keywords, focusing on low-competition, high-volume opportunities, while also producing content that is not only easy to comprehend but also optimized for search engine ranking and designed to draw in targeted traffic effectively. Ultimately, IvaBot empowers its users to elevate their online presence with data-driven strategies and creative solutions.

PapaProxy.net specializes in providing wholesale datacenter (IPv4) and ISP (static residential) proxies tailored for teams engaged in extensive data collection and analysis efforts, including activities such as scraping, price tracking, market research, AI data gathering, advertisement verification, and managing multiple accounts through professional processes. Established in 2019 by Alex Young, who faced challenges in finding dependable high-volume proxies at reasonable rates, the company operates under the philosophy that investment is prioritized in infrastructure rather than marketing, allowing cost savings to be passed on to clients. This approach is reflected in the use of robust server systems powered by cutting-edge AMD EPYC CPUs, ensuring that lower prices do not compromise the quality of service provided. The focus is on catering to experienced users who understand their requirements, offering them stable proxies, personalized support, and competitive pricing that makes large-scale data collection economically viable. By maintaining this commitment to quality and service excellence, PapaProxy.net has established itself as a trusted ally in the data collection landscape.

Zzz is a comprehensive platform likened to "Shopify for mobile applications," enabling users to effortlessly create a mobile app, launch it on the App Store, and monetize it without any coding knowledge. Simply share your concept with the AI, and Zzz instantly crafts the architecture, user interfaces, and functionality, eliminating the need for setup or programming—just your idea is enough to get started. Designed for transforming a single prompt into a fully functional app, it empowers users to develop a wide range of applications, such as games, dating platforms, tracking tools, AI coaches, productivity enhancers, and marketplaces. Additionally, Zzz manages the entire launch process, including submission to the App Store, creation of screenshots, and writing ASO descriptions, allowing users to seamlessly transition from an initial idea to a live application with minimal hassle. It also produces a professional-grade design right from the outset, incorporating logos, color schemes, icons, and screen layouts to ensure a cohesive look without requiring a designer. Furthermore, Zzz automatically generates marketing materials, such as screenshots, compelling descriptions, and ASO-optimized titles in multiple languages, making it easier for users to promote their apps globally. This innovative approach not only streamlines the app development process but also opens new avenues for creativity and entrepreneurship, catering to a diverse range of ideas and industries.

Gemini 3.5 Flash-Lite stands out as the quickest model within Google's Gemini 3.5 lineup, specifically engineered for tasks requiring low latency and for enhancing developer workflows that demand high throughput, including agentic search, document processing, coding, and extensive data analysis. It boasts an impressive output capacity of 350 tokens per second and marks a significant enhancement over earlier Flash-Lite iterations in terms of both quality and agentic capabilities. Developers have the flexibility to adjust the model's thinking level to suit the demands of the task at hand: minimal or low thinking allows for rapid processing of large volumes, while elevated thinking levels accommodate more intricate, multi-step workflows involving subagents. Furthermore, the model is equipped with built-in computational skills, enabling it to interact effectively with various digital environments across compatible platforms. Additionally, Gemini 3.5 Flash-Lite excels in coding, comprehending long contexts, and executing real-world tasks, consistently outperforming its predecessor, Gemini 3.1 Flash-Lite, in critical assessments and even exceeding the performance of Gemini 3 Flash on multiple benchmarks related to agentic functions and software engineering. This impressive performance highlights its potential to transform how developers approach complex workflows and data-intensive tasks.

Transform your existing infrastructure into an asset for the entire company with a platform that makes identity a business enabler. RadiantOne is a cornerstone for complex identity infrastructures. Using intelligent integration, you can improve your business outcomes, security and compliance posture, speed-to-market and more. RadiantOne allows companies to avoid custom coding, rework and ongoing maintenance in order to integrate new initiatives with existing environments. The deployment of expensive solutions is not on time or within budget, which negatively impacts ROI and causes employee frustration. Identity frameworks which cannot scale are a waste of time and resources. Employees struggle to provide new solutions for users. Rigid and static systems cannot meet changing requirements. This leads to duplication of efforts and repeated processes.

JavaScript serves as both a scripting and programming language used extensively on the web, allowing developers to create interactive and dynamic web features. A staggering 97% of websites globally utilize client-side JavaScript, underscoring its significance in web development. As one of the premier scripting languages available, JavaScript has become essential for building engaging user experiences online. In JavaScript, strings are defined using either single quotation marks '' or double quotation marks "", and it's crucial to remain consistent with whichever style you choose. If you open a string with a single quote, you must close it with a single quote as well. Each quotation style has its advantages and disadvantages; for instance, single quotes can simplify the inclusion of HTML within JavaScript since it eliminates the need to escape double quotes. This becomes particularly relevant when incorporating quotation marks inside a string, prompting you to use opposing quotation styles for clarity and correctness. Ultimately, understanding how to effectively manage strings in JavaScript is vital for any developer looking to enhance their coding skills.

SQL is a specialized programming language designed specifically for the purpose of retrieving, organizing, and modifying data within relational databases and the systems that manage them. Its use is essential for effective database management and interaction.

C#, often referred to as "C Sharp," is a contemporary programming language characterized by its object-oriented and type-safe nature. This language allows developers to create a wide array of secure and efficient applications that operate within the .NET framework. With foundations in the C language family, programmers familiar with C, C++, Java, and JavaScript will find C# to be quite accessible. This guide offers a comprehensive overview of the essential elements of C# up to version 8. As an object-oriented and component-oriented language, C# includes specific constructs that facilitate the development and utilization of software components. Over time, C# has evolved by incorporating features that cater to new workloads and progressive software design methodologies. At its essence, C# embodies object-oriented principles, enabling developers to define types along with their associated behaviors while fostering a rich ecosystem for application development. The language continues to adapt and grow, ensuring its relevance in the ever-changing landscape of technology.

YAML stands for "YAML Ain't Markup Language" and serves as a user-friendly data serialization format that is compatible with various programming languages. Its design prioritizes readability and ease of use for developers.

Bash is an open-source Unix shell and command language that has gained popularity as the standard login shell for numerous Linux distributions. Not only is it accessible on Linux platforms, but a version can also be utilized on Windows via the Windows Subsystem for Linux. Furthermore, Bash serves as the default user shell in Solaris 11 and was the primary shell for Apple’s macOS until version 10.3, when it was replaced by zsh in macOS Catalina; however, Bash continues to be offered as an alternative shell option for macOS users. As a powerful command processor, Bash enables users to input commands in a text-based interface that the system executes, while it can also read and run commands from a file, referred to as a shell script. Among its extensive features, Bash includes support for wildcard matching, piping, here documents, command substitution, variables, and various control structures for testing conditions and iterating processes. Moreover, Bash adheres to the POSIX shell standards, ensuring compatibility across different Unix-like systems. Its versatility makes Bash a preferred choice for both novice and experienced users alike.

LearnLM is a novel, experimental model tailored for specific tasks, developed to align with the principles of learning science for enhanced teaching and learning experiences. It is adept at following system prompts such as "You are an expert tutor," and promotes active engagement in learning by facilitating practice and offering timely feedback. By effectively managing cognitive load, the model delivers pertinent and well-organized information through various modalities, while also adjusting to the individual learner’s objectives and requirements, grounding its responses in suitable resources. Furthermore, LearnLM encourages curiosity, sustaining learner motivation throughout their educational pursuits, and fosters metacognitive skills by assisting learners in planning, monitoring, and reflecting on their academic progress. This groundbreaking model is currently accessible for experimentation within AI Studio, allowing educators and researchers to explore its potential in real-world applications. Ultimately, LearnLM represents a significant step forward in the integration of AI within educational contexts.

Gemini 2.5 Pro Preview (I/O Edition) offers cutting-edge AI tools for developers, designed to simplify coding and improve web app creation. This version of the Gemini AI model excels in code editing, transformation, and error reduction, making it an invaluable asset for developers. Its advanced performance in video understanding and web development tasks ensures that you can create both beautiful and functional web apps. Available via Google’s AI platforms, Gemini 2.5 Pro Preview helps you streamline your workflow with smarter, faster coding and reduced errors for a more efficient development process.

Orq.ai stands out as the leading platform tailored for software teams to effectively manage agentic AI systems on a large scale. It allows you to refine prompts, implement various use cases, and track performance meticulously, ensuring no blind spots and eliminating the need for vibe checks. Users can test different prompts and LLM settings prior to launching them into production. Furthermore, it provides the capability to assess agentic AI systems within offline environments. The platform enables the deployment of GenAI features to designated user groups, all while maintaining robust guardrails, prioritizing data privacy, and utilizing advanced RAG pipelines. It also offers the ability to visualize all agent-triggered events, facilitating rapid debugging. Users gain detailed oversight of costs, latency, and overall performance. Additionally, you can connect with your preferred AI models or even integrate your own. Orq.ai accelerates workflow efficiency with readily available components specifically designed for agentic AI systems. It centralizes the management of essential phases in the LLM application lifecycle within a single platform. With options for self-hosted or hybrid deployment, it ensures compliance with SOC 2 and GDPR standards, thereby providing enterprise-level security. This comprehensive approach not only streamlines operations but also empowers teams to innovate and adapt swiftly in a dynamic technological landscape.

ProAI is an innovative platform that utilizes artificial intelligence to assist entrepreneurs and startups in swiftly crafting detailed business plans that are ready for investors. By simply responding to a set of questions, users can generate a personalized business plan that includes essential components such as financial projections, market analysis, and strategic recommendations. The platform provides tailored financial models that can be exported to Excel, covering critical documents like profit and loss statements, cash flow assessments, balance sheets, and vital performance indicators. Drawing from insights gained through more than 3,600 client projects, ProAI offers customized marketing, sales, and product strategies to its users. Moreover, it features an AI Business Advisor that delivers individualized suggestions, access to a vast database of over 160,000 potential investors, and tools for developing pitch decks and performing market research. The user-friendly design and the ability to integrate with various data sources enhance the overall efficiency of the business planning experience, making it accessible even for those new to entrepreneurship. Consequently, ProAI not only saves time but also empowers users to make informed decisions while strategizing for their business ventures.

Introducing Gemma 3n, our cutting-edge open multimodal model designed specifically for optimal on-device performance and efficiency. With a focus on responsive and low-footprint local inference, Gemma 3n paves the way for a new generation of intelligent applications that can be utilized on the move. It has the capability to analyze and respond to a blend of images and text, with plans to incorporate video and audio functionalities in the near future. Developers can create smart, interactive features that prioritize user privacy and function seamlessly without an internet connection. The model boasts a mobile-first architecture, significantly minimizing memory usage. Co-developed by Google's mobile hardware teams alongside industry experts, it maintains a 4B active memory footprint while also offering the flexibility to create submodels for optimizing quality and latency. Notably, Gemma 3n represents our inaugural open model built on this revolutionary shared architecture, enabling developers to start experimenting with this advanced technology today in its early preview. As technology evolves, we anticipate even more innovative applications to emerge from this robust framework.

The Gemini Embedding's inaugural text model, known as gemini-embedding-001, is now officially available through the Gemini API and Gemini Enterprise Agent Platform, having maintained its leading position on the Massive Text Embedding Benchmark Multilingual leaderboard since its experimental introduction in March, attributed to its outstanding capabilities in retrieval, classification, and various embedding tasks, surpassing both traditional Google models and those from external companies. This highly adaptable model accommodates more than 100 languages and has a maximum input capacity of 2,048 tokens, utilizing the innovative Matryoshka Representation Learning (MRL) method, which allows developers to select output dimensions of 3072, 1536, or 768 to ensure the best balance of quality, performance, and storage efficiency. Developers are able to utilize it via the familiar embed_content endpoint in the Gemini API.

Airia’s enterprise AI orchestration platform effortlessly connects with current systems and data sources while providing a no-code agent builder that allows for quick prototyping. It features pre-built connectors for cohesive data integration, along with intelligent AI operations that enhance both performance and cost efficiency through smart routing and centralized lifecycle management. The platform also emphasizes enterprise-grade security and governance, including comprehensive audit capabilities and responsible AI guardrails. Being model-agnostic and vendor-neutral, it allows for adaptable deployment options across shared or dedicated cloud, private cloud, and on-premises setups. This flexibility empowers both technical and non-technical users to construct, implement, and oversee secure AI agents on a large scale without the need for intricate installations or migrations. With its user-friendly interface and cohesive platform, Airia revolutionizes workflows across various departments, including engineering, IT, finance, legal, marketing, sales, and support, enabling organizations to confidently and compliantly advance their AI initiatives. Ultimately, this comprehensive solution positions businesses to harness the full potential of AI while streamlining operations and ensuring security.

The Gemini 2.5 Flash Image is Google's cutting-edge model for image creation and modification, now available through the Gemini API, build mode in Google AI Studio, and Gemini Enterprise Agent Platform. This model empowers users with remarkable creative flexibility, allowing them to seamlessly merge various input images into one cohesive visual, ensure character or product consistency throughout edits for enhanced storytelling, and execute detailed, natural-language transformations such as object removal, pose adjustments, color changes, and background modifications. Drawing from Gemini’s extensive knowledge of the world, the model can comprehend and reinterpret scenes or diagrams contextually, paving the way for innovative applications like educational tutors and scene-aware editing tools. Showcased through customizable template applications in AI Studio, which includes features such as photo editors, multi-image merging, and interactive tools, this model facilitates swift prototyping and remixing through both prompts and user interfaces. With its advanced capabilities, Gemini 2.5 Flash Image is set to revolutionize the way users approach creative visual projects.

Gemini Image Pro is an advanced multimodal system for generating and editing images, allowing users to craft, modify, and enhance visuals using natural language prompts or by integrating various input images. This platform ensures uniformity in character and object representation throughout edits and offers detailed local modifications, including background blurring, object removal, style transfers, or pose alterations, all while leveraging inherent world knowledge for contextually relevant results. Furthermore, it facilitates the fusion of multiple images into a single, cohesive new visual and prioritizes design workflow elements, featuring template-based outputs, consistency in brand assets, and the ability to maintain recurring character or style appearances across different scenes. Additionally, the system incorporates digital watermarking to identify AI-generated images and is accessible via Gemini API, Google AI Studio, and Gemini Enterprise Agent Platform, making it a versatile tool for creators across various industries. With its robust capabilities, Gemini Image Pro is set to revolutionize the way users interact with image generation and editing technologies.

Gemini 3 Flash is a next-generation AI model created to deliver powerful intelligence without sacrificing speed. Built on the Gemini 3 foundation, it offers advanced reasoning and multimodal capabilities with significantly lower latency. The model adapts its thinking depth based on task complexity, optimizing both performance and efficiency. Gemini 3 Flash is engineered for agentic workflows, iterative development, and real-time applications. Developers benefit from faster inference and strong coding performance across benchmarks. Enterprises can deploy it at scale through Vertex AI and Gemini Enterprise. Consumers experience faster, smarter assistance across the Gemini app and Search. Gemini 3 Flash makes high-performance AI practical for everyday use.

Veo 3.1 Lite is an advanced yet cost-efficient video generation model from Google DeepMind, designed to help developers create AI-generated videos at scale. It supports both text-to-video and image-to-video generation, enabling flexible content creation for various applications. The model delivers the same speed as higher-tier versions while significantly reducing costs, making it ideal for high-volume use cases. It supports multiple aspect ratios, including landscape (16:9) and portrait (9:16), along with resolutions up to 1080p. Developers can also customize video duration, choosing between different lengths to match their needs. Veo 3.1 Lite is integrated into the Gemini API and Google AI Studio, allowing easy access and implementation. Its balance of performance and affordability makes it suitable for a wide range of applications. The model is designed to support scalable video workflows without compromising quality. It also provides flexibility for developers building creative, marketing, or product-based solutions. Overall, Veo 3.1 Lite empowers developers to integrate video generation into their platforms efficiently and cost-effectively.

Gemini Robotics-ER 1.6 represents a suite of AI models created by Google DeepMind, designed to infuse sophisticated multimodal intelligence into the tangible world by empowering robots to sense, analyze, and act within real-world settings. Based on the Gemini 2.0 architecture, it enhances conventional AI abilities by incorporating physical actions as a form of output, thus enabling robots to not only understand visual data but also to follow natural language commands, translating these inputs directly into motor functions for task execution. This system features a vision-language-action model that interprets both images and directives to carry out tasks effectively, alongside an additional embodied reasoning model (Gemini Robotics-ER) that focuses on spatial awareness, strategic planning, and decision-making in physical contexts. Through these capabilities, the models allow robots to adapt to unfamiliar scenarios, objects, and environments, thereby enabling them to tackle intricate, multi-step tasks even when they have not undergone specific training for such challenges. Ultimately, this innovation represents a significant leap towards creating robots that can seamlessly integrate and operate within the complexities of everyday life.

Keytail is an innovative content engine driven by AI, designed to assist brands in becoming the definitive source of information across various search platforms, including Google, ChatGPT, Perplexity, and Google AI. Rather than concentrating solely on keywords, Keytail uncovers the genuine inquiries that audiences are posing on platforms like Google, People Also Ask, and LLM queries, subsequently generating AEO-optimized content automatically so that brands can secure their place in the trusted answers users seek. The platform oversees the entire content development process, guiding users from the initial question identification to content generation, publishing, and performance analysis. It pinpoints the most valuable questions to address, meticulously crafts each article to ensure it stands out as the best answer available, and organizes content in a way that is compatible with both Google and LLMs, incorporating clear hierarchies, metadata, schema, FAQs, and inherent usefulness. In addition, Keytail features an editor tailored for purposeful refinement, equipped with slash commands that allow users to rewrite, condense, expand, and enhance their content based on genuine user intent, thus ensuring that the content remains relevant and engaging over time. By leveraging such advanced functionalities, Keytail empowers brands to maintain a competitive edge in the digital landscape.

Enhance the capabilities of your preferred Google applications, such as Calendar, Docs, Drive, Gmail, Sheets, and Slides, by utilizing Apps Script, which operates on a contemporary JavaScript framework hosted in the cloud. This tool allows you to develop solutions that significantly improve both collaboration and productivity. Begin your journey by checking out a series of guided codelab tutorials designed to introduce you to the fundamentals of Apps Script specifically tailored for Google Sheets. Once you've completed the codelab, you can jump into one of our quickstart projects to swiftly construct a functional script. With Apps Script, you can design custom menus and functions in Google Sheets, handle responses efficiently in Google Forms, or even develop a basic add-on for Google Docs or a bot for Hangouts Chat! Furthermore, Apps Script simplifies the process of creating and sharing add-ons across Google Docs, Sheets, Slides, and Forms. It provides an efficient means to distribute your scripts to a broad audience, whether your goal is to share your code with the entire globe or to restrict access to just the users within your Google Workspace domain. This flexibility ensures that you can tailor your scripts to meet specific needs while maintaining control over their distribution.

C++ is known for its straightforward and lucid syntax. While a novice programmer might find C++ somewhat more obscure than other languages due to its frequent use of special symbols (like {}[]*&!|...), understanding these symbols can actually enhance clarity and structure, making it more organized than languages that depend heavily on verbose English syntax. Additionally, the input/output system of C++ has been streamlined compared to C, and the inclusion of the standard template library facilitates data handling and communication, making it as user-friendly as other programming languages without sacrificing functionality. This language embraces an object-oriented programming paradigm, viewing software components as individual objects with distinct properties and behaviors, which serves to enhance or even replace the traditional structured programming approach that primarily centered around procedures and parameters. Ultimately, this focus on objects allows for greater flexibility and scalability in software development.

Develop a fully matured async-await mechanism for user interfaces that feature event-driven programming, integrated with isolate-based concurrency. This programming language is tailored for crafting user interfaces and includes enhancements like robust null safety, a spread operator for expanding collections, and a collection if statement for platform-specific UI customization. It allows for coding with a versatile type system that offers extensive static analysis alongside advanced, customizable tools. You can aim for web deployment using complete, mature, and efficient compilers designed for JavaScript. Additionally, backend functionalities can be implemented in the same programming language that powers your app. This overview serves as a preliminary introduction to the language, particularly for those who prefer learning through practical examples. For further insights, exploring the language and library tours or the Dart cheatsheet codelab would be highly beneficial. Moreover, engaging with community resources can enhance your understanding and proficiency even more.

Gemma represents a collection of cutting-edge, lightweight open models that are built upon the same research and technology underlying the Gemini models. Created by Google DeepMind alongside various teams at Google, the inspiration for Gemma comes from the Latin word "gemma," which translates to "precious stone." In addition to providing our model weights, we are also offering tools aimed at promoting developer creativity, encouraging collaboration, and ensuring the ethical application of Gemma models. Sharing key technical and infrastructural elements with Gemini, which stands as our most advanced AI model currently accessible, Gemma 2B and 7B excel in performance within their weight categories when compared to other open models. Furthermore, these models can conveniently operate on a developer's laptop or desktop, demonstrating their versatility. Impressively, Gemma not only outperforms significantly larger models on crucial benchmarks but also maintains our strict criteria for delivering safe and responsible outputs, making it a valuable asset for developers.

The Gemma family consists of advanced, lightweight models developed using the same innovative research and technology as the Gemini models. These cutting-edge models are equipped with robust security features that promote responsible and trustworthy AI applications, achieved through carefully curated data sets and thorough refinements. Notably, Gemma models excel in their various sizes—2B, 7B, 9B, and 27B—often exceeding the performance of some larger open models. With the introduction of Keras 3.0, users can experience effortless integration with JAX, TensorFlow, and PyTorch, providing flexibility in framework selection based on specific tasks. Designed for peak performance and remarkable efficiency, Gemma 2 is specifically optimized for rapid inference across a range of hardware platforms. Furthermore, the Gemma family includes diverse models that cater to distinct use cases, ensuring they adapt effectively to user requirements. These lightweight language models feature a decoder and have been trained on an extensive array of textual data, programming code, and mathematical concepts, which enhances their versatility and utility in various applications.

Gemini 2.0 Flash Thinking is an innovative artificial intelligence model created by Google DeepMind, aimed at improving reasoning abilities through the clear articulation of its thought processes. This openness enables the model to address intricate challenges more efficiently while offering users straightforward insights into its decision-making journey. By revealing its internal reasoning, Gemini 2.0 Flash Thinking not only boosts performance but also enhances explainability, rendering it an essential resource for applications that necessitate a profound comprehension and confidence in AI-driven solutions. Furthermore, this approach fosters a deeper relationship between users and the technology, as it demystifies the workings of AI.

Gemini 2.0 Flash-Lite represents the newest AI model from Google DeepMind, engineered to deliver an affordable alternative while maintaining high performance standards. As the most budget-friendly option within the Gemini 2.0 range, Flash-Lite is specifically designed for developers and enterprises in search of efficient AI functions without breaking the bank. This model accommodates multimodal inputs and boasts an impressive context window of one million tokens, which enhances its versatility for numerous applications. Currently, Flash-Lite is accessible in public preview, inviting users to investigate its capabilities for elevating their AI-focused initiatives. This initiative not only showcases innovative technology but also encourages feedback to refine its features further.

Gemini 2.0 Pro stands as the pinnacle of Google DeepMind's AI advancements, engineered to master intricate tasks like programming and complex problem resolution. As it undergoes experimental testing, this model boasts an impressive context window of two million tokens, allowing for the efficient processing and analysis of extensive data sets. One of its most remarkable attributes is its ability to integrate effortlessly with external tools such as Google Search and code execution platforms, which significantly boosts its capacity to deliver precise and thorough answers. This innovative model signifies a major leap forward in artificial intelligence, equipping both developers and users with a formidable tool for addressing demanding challenges. Furthermore, its potential applications span various industries, making it a versatile asset in the evolving landscape of AI technology.

Gemini 2.5 Flash is a high-performance AI model developed by Google to meet the needs of businesses requiring low-latency responses and cost-effective processing. It is optimized for real-time applications like customer support and virtual assistants, where responsiveness is crucial. Gemini 2.5 Flash features dynamic reasoning, which allows businesses to fine-tune the model's speed and accuracy to meet specific needs. By adjusting the "thinking budget" for each query, it helps companies achieve optimal performance without sacrificing quality.

The Gemini Live API is an advanced preview feature designed to facilitate low-latency, bidirectional interactions through voice and video with the Gemini system. This innovation allows users to engage in conversations that feel natural and human-like, while also enabling them to interrupt the model's responses via voice commands. In addition to handling text inputs, the model is capable of processing audio and video, yielding both text and audio outputs. Recent enhancements include the introduction of two new voice options and support for 30 additional languages, along with the ability to configure the output language as needed. Furthermore, users can adjust image resolution settings (66/256 tokens), decide on turn coverage (whether to send all inputs continuously or only during user speech), and customize interruption preferences. Additional features encompass voice activity detection, new client events for signaling the end of a turn, token count tracking, and a client event for marking the end of the stream. The system also supports text streaming, along with configurable session resumption that retains session data on the server for up to 24 hours, and the capability for extended sessions utilizing a sliding context window for better conversation continuity. Overall, Gemini Live API enhances interaction quality, making it more versatile and user-friendly.

Gemini 2.5 Pro Deep Think is the latest evolution of Google’s Gemini models, specifically designed to tackle more complex tasks with better accuracy and efficiency. The key feature of Deep Think enables the AI to think through its responses, improving its reasoning and enhancing decision-making processes. This model is a game-changer for coding, problem-solving, and AI-driven conversations, with support for multimodality, long context windows, and advanced coding capabilities. It integrates native audio outputs for richer, more expressive interactions and is optimized for speed and accuracy across various benchmarks. With the addition of this advanced reasoning mode, Gemini 2.5 Pro Deep Think is not just faster but also smarter, handling complex queries with ease.

Lyria 2 is an innovative music generation tool developed by Google, built to empower musicians with high-fidelity sound and professional-grade audio. With its ability to create intricate and detailed compositions across genres such as classical, jazz, pop, and electronic, Lyria 2 allows users to control key elements of their music like key and BPM, giving them granular creative control. Musicians can use text prompts to generate custom music, accelerating the composition process by providing new starting points and refining ideas quickly. Lyria 2 also helps uncover new musical styles and techniques, encouraging exploration beyond familiar genres. By generating music with stunning nuance and realism, it opens new creative avenues for artists to experiment with melodies, harmonies, and arrangements, whether they're looking to refine existing compositions or craft entirely new pieces.

WeatherNext represents a suite of AI-driven models developed by Google DeepMind and Google Research, designed to deliver cutting-edge weather predictions. These advanced models surpass conventional physics-based approaches in both speed and efficiency, leading to enhanced reliability in forecasts. By improving the accuracy of weather predictions, these innovations could significantly aid in disaster preparedness, ultimately saving lives during severe weather scenarios and bolstering the dependability of renewable energy sources and supply chains. WeatherNext Graph stands out by providing more precise and efficient deterministic forecasts than existing systems, producing a single forecast for each specified time and location with a 6-hour temporal resolution and a 10-day lead time. In addition, WeatherNext Gen excels at generating ensemble forecasts that outshine the current predominant models, thereby equipping decision-makers with a clearer understanding of weather uncertainties and the associated risks of extreme weather conditions. This leap in forecasting capability promises to transform how we respond to and manage the impacts of climate variability.

Gemini 2.5, developed by Google DeepMind, represents a breakthrough in AI with enhanced reasoning capabilities and native multimodality, allowing it to process long context windows of up to one million tokens. The family includes three variants: Pro for complex coding tasks, Flash for fast general use, and Flash-Lite for high-volume, cost-efficient workflows. Gemini 2.5 models improve accuracy by thinking through diverse strategies and provide developers with adaptive controls to optimize performance and resource use. The models handle multiple input types—text, images, video, audio, and PDFs—and offer powerful tool use like search and code execution. Gemini 2.5 achieves state-of-the-art results across coding, math, science, reasoning, and multilingual benchmarks, outperforming its predecessors. It is accessible through Google AI Studio, Gemini API, and Vertex AI platforms. Google emphasizes responsible AI development, prioritizing safety and security in all applications. Gemini 2.5 enables developers to build advanced interactive simulations, automated coding, and other innovative AI-driven solutions.

Gemini Robotics integrates Gemini's advanced multimodal reasoning and comprehension of the world into tangible applications, empowering robots of various forms and sizes to undertake a diverse array of real-world activities. Leveraging the capabilities of Gemini 2.0, it enhances sophisticated vision-language-action models by enabling reasoning about physical environments, adapting to unfamiliar scenarios, including novel objects, various instructions, and different settings, while also comprehending and reacting to everyday conversational requests. Furthermore, it exhibits the ability to adjust to abrupt changes in commands or surroundings without requiring additional input. The dexterity module is designed to tackle intricate tasks that demand fine motor skills and accurate manipulation, allowing robots to perform activities like folding origami, packing lunch boxes, and preparing salads. Additionally, it accommodates multiple embodiments, ranging from bi-arm platforms like ALOHA 2 to humanoid robots such as Apptronik’s Apollo, making it versatile across various applications. Optimized for local execution, it includes a software development kit (SDK) that facilitates smooth adaptation to new tasks and environments, ensuring that these robots can evolve alongside emerging challenges. This flexibility positions Gemini Robotics as a pioneering force in the robotics industry.

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.

Veo 3.1 Fast represents a major leap forward in generative video technology, combining the creative intelligence of Veo 3.1 with faster generation times and expanded control. Available through the Gemini API, the model turns written prompts and still images into cinematic videos with synchronized sound and expressive storytelling. Developers can guide scene generation using up to three reference images, extend video length continuously with “Scene Extension,” and even create dynamic transitions between first and last frames. Its enhanced AI engine maintains character and visual consistency across sequences while improving adherence to user intent and narrative tone. Veo 3.1 Fast’s audio generation adds depth with natural voices and realistic soundscapes, enabling richer, more immersive outputs. Integration with Google AI Studio and Gemini Enterprise Agent Platform makes it simple to build, test, and deploy creative applications. Leading creative teams, such as Promise Studios and Latitude, are already using Veo 3.1 Fast for generative filmmaking and interactive storytelling. Offering the same price as Veo 3.0 but vastly improved capability, it sets a new benchmark for AI-driven video production.