Google Gemini: A Complete Guide to the AI Apps & Models

Understanding Google's Gemini AI

Google is actively developing and releasing Gemini, a comprehensive collection of generative AI models, applications, and related services. This initiative represents a significant push into the rapidly evolving field of artificial intelligence.

But what exactly is Gemini? And what are the practical applications for users? Furthermore, how does its performance compare to established generative AI platforms like OpenAI’s ChatGPT, Meta’s Llama, and Microsoft’s Copilot?

A Comprehensive Guide to Gemini

Keeping abreast of the continuous advancements in Gemini can be challenging. Therefore, we have compiled this resource to provide a clear and concise overview.

This guide will be regularly updated to reflect new Gemini models, feature additions, and any announcements regarding Google’s future strategies for the platform.

Gemini's Core Components

• Gemini Models: These are the foundational AI engines powering the various Gemini applications.
• Gemini Apps: These are user-facing tools built upon the Gemini models, designed for specific tasks.
• Gemini Services: These provide the infrastructure and APIs for developers to integrate Gemini into their own projects.

The goal is to offer a versatile AI ecosystem capable of handling a wide range of tasks, from text generation to image creation and beyond.

Understanding these core components is crucial for grasping the full scope of Google’s Gemini project and its potential impact on the AI landscape.

Introducing Gemini: Google's Advanced AI

Gemini represents Google's highly anticipated, next-generation family of generative AI models. Its development stems from the collaborative efforts of DeepMind and Google Research, both leading AI research divisions within Google.

The Gemini family is comprised of several distinct models, each tailored for specific applications and performance characteristics.

Gemini Model Variants

• Gemini Ultra: This is the largest and most powerful model within the Gemini family.
• Gemini Pro: A large-scale model, though smaller in size compared to Ultra. Gemini 2.0 Pro currently serves as Google’s primary flagship offering.
• Gemini Flash: Designed for speed, this version is a streamlined and “distilled” iteration of the Pro model.
• Gemini Flash-Lite: Offering a balance of speed and efficiency, it’s a slightly reduced and faster version of Gemini Flash.
• Gemini Flash Thinking: This model incorporates advanced “reasoning” capabilities for more complex tasks.
• Gemini Nano: Two compact models, Nano-1 and the enhanced Nano-2, are designed for on-device, offline operation.

A key feature of all Gemini models is their native multimodality. This means they are capable of processing and analyzing data beyond just text.

Google states that these models underwent pre-training and fine-tuning utilizing a diverse range of publicly available, proprietary, and licensed data. This includes audio, images, videos, codebases, and text across multiple languages.

This multimodal approach distinguishes Gemini from earlier models like Google’s LaMDA, which was exclusively trained on textual data. LaMDA’s capabilities were limited to text-based outputs, such as essays and emails.

In contrast, Gemini models, particularly the latest versions of Gemini Flash and Gemini Pro, can natively generate outputs in multiple formats, including images and audio, alongside text.

It’s important to acknowledge the ongoing discussions surrounding the ethics and legality of training AI models on publicly sourced data, especially when done without explicit consent from data owners. Google provides an AI indemnification policy for some Google Cloud users, but it includes specific limitations.

Therefore, careful consideration is advised, particularly when deploying Gemini for commercial purposes.

Understanding the Distinction Between Gemini Applications and Gemini Models

It's important to recognize that Gemini exists as a separate entity from the Gemini applications available on both web and mobile platforms, previously known as Bard.

The Gemini applications function as interfaces, connecting users to a range of Gemini models. They provide a conversational experience built upon Google’s generative AI capabilities. This is comparable to platforms like ChatGPT and the Claude suite of applications developed by Anthropic.

Access to Gemini on the web can be found here. For Android users, the Gemini application now takes the place of the former Google Assistant application.

On iOS devices, the Google and Google Search applications serve as the client interfaces for accessing Gemini’s functionalities.

Android users benefit from a Gemini overlay, allowing for direct questioning regarding on-screen content, such as a YouTube video. This overlay is activated by a long press of the power button or by using the “Hey Google” voice command.

Gemini applications are versatile, accepting input through images, voice, and text. They also support file uploads, including PDFs sourced from Google Drive, and are capable of generating images.

Conversations initiated within the Gemini applications on mobile devices are synchronized with Gemini on the web, provided the user is logged in with the same Google Account across both platforms.

Key Differences Summarized

• Gemini Models: The underlying AI engines powering the functionality.
• Gemini Apps: User-facing applications that provide access to these models.

Essentially, the apps are the means of interaction, while the models represent the intelligence behind the responses.

Gemini Advanced: A Comprehensive Overview

Access to Gemini's capabilities isn't limited to the dedicated Gemini applications. Increasingly, features powered by Gemini are being integrated directly into frequently used Google applications and services, such as Gmail and Google Docs.

Utilizing many of these integrated features requires a subscription to the Google One AI Premium Plan. This plan, functioning as an extension of Google One, is priced at $20 per month and unlocks Gemini’s functionality within Google Workspace applications including Docs, Maps, Slides, Sheets, Drive, and Meet.

Unlocking Advanced Features

The AI Premium Plan also provides access to Gemini Advanced. This unlocks the use of Google’s most powerful Gemini models within the Gemini applications themselves.

Subscribers to Gemini Advanced receive additional benefits. These include prioritized access to the latest features and model updates, the ability to execute and modify Python code directly within the Gemini interface, and expanded limits for NotebookLM.

NotebookLM is Google’s innovative tool designed to transform PDF documents into AI-generated podcasts. A recent enhancement to Gemini Advanced is the introduction of a memory function.

Key Capabilities of Gemini Advanced

This memory feature retains user preferences and enables Gemini to utilize past conversations as contextual information for ongoing interactions.

A particularly noteworthy exclusive feature for Gemini Advanced is Deep Research. This tool employs Gemini models with enhanced reasoning abilities to generate in-depth reports.

Upon receiving a user prompt – for example, “What are the best strategies for renovating my kitchen?” – Deep Research formulates a structured research plan and conducts web searches to deliver a thorough and well-supported response.

• It develops a multi-step research plan.
• It searches the web for relevant information.
• It crafts a comprehensive answer based on its findings.

Gemini's Expanding Integration Across Google Services

Gemini is now integrated into a variety of Google applications, beginning with Gmail. Within Gmail, it operates through a side panel, facilitating email composition and providing summaries of existing conversations.

This same side panel functionality is also available in Google Docs. Here, Gemini assists with content creation, refinement, and the generation of novel concepts.

Gemini extends its capabilities to Google Slides, where it can automatically generate presentation slides and create custom imagery to enhance visual communication.

Furthermore, Gemini is utilized within Google Sheets to efficiently track and organize data. It streamlines processes by creating tables and formulating complex formulas.

Applications in Navigation, Storage, and Browsing

The integration of Gemini reaches Google Maps, where it consolidates reviews for local businesses. It also offers personalized recommendations, such as itineraries for exploring new cities.

Google Drive also benefits from Gemini's abilities. It can summarize files and folders, and quickly provide key information regarding projects.

Recently, Gemini was added to the Google Chrome browser as an AI-powered writing assistant. This tool enables users to create new content or revise existing text, leveraging the context of the current webpage for relevant suggestions.

Expanding Reach into Developer Tools and Security

Hints of Gemini are appearing in Google’s database solutions, cloud security applications, and application development platforms like Firebase and Project IDX.

Its influence is also felt in consumer-facing apps such as Google Photos, where it processes natural language search requests, YouTube, aiding in video idea generation, and Meet, providing real-time caption translation.

Code Assist, previously known as Duet AI for Developers, now leverages Gemini for more powerful code completion and generation. This offloads significant processing demands to the AI model.

Google’s security products, including Gemini in Threat Intelligence, are also enhanced by Gemini. This allows for the analysis of large volumes of potentially harmful code and enables users to search for threats using natural language.

Gemini Capabilities: Gems and Extensions

Users of Gemini Advanced have the ability to develop Gems, which are essentially personalized chatbots. These custom chatbots function on both desktop and mobile platforms and are driven by the Gemini models.

Gems are created using simple, everyday language descriptions. For example, a user could define a Gem as, “You are a personal fitness instructor; provide me with a daily workout schedule.” These creations can then be shared publicly or maintained for individual use.

Leveraging Gemini Extensions

The Gemini applications are designed to connect with various Google services through features known as Gemini extensions.

This integration allows Gemini to access and utilize information from platforms like Drive, Gmail, and YouTube. Consequently, it can effectively address requests such as, “Can you provide a summary of my most recent email correspondence?”

The extensions enhance Gemini’s functionality by enabling it to draw upon data from a user’s existing Google ecosystem.

• Gems offer a personalized chatbot experience.
• Gemini extensions facilitate integration with core Google services.

These features collectively contribute to a more versatile and integrated AI experience for Gemini users.

Gemini Live: Enhanced Voice Interaction

A new feature, known as Gemini Live, facilitates extended and detailed voice conversations with the Gemini AI. This functionality is currently integrated within the Gemini mobile applications and is also accessible through the Pixel Buds Pro 2.

Notably, access to Gemini Live remains available even when the user’s mobile device is locked, providing continuous interaction.

Interactive and Adaptive Conversations

When Gemini Live is active, users have the ability to interject during the chatbot’s responses to request further clarification.

The system is engineered to dynamically adjust to the user’s speaking style as the conversation progresses, creating a more natural flow.

Utilizing Gemini Live as a Virtual Assistant

Beyond simple conversation, Gemini Live functions as a supportive virtual coach.

It can assist with preparation for various scenarios, including idea generation and practice sessions.

For example, the tool can offer guidance on emphasizing relevant skills during a job interview and provide constructive feedback on public speaking techniques.

A comprehensive evaluation of Gemini Live can be found in our detailed review.

Gemini Designed for Teen Users

Google has introduced a specialized Gemini version geared towards adolescent users and students.

This iteration of Gemini incorporates “enhanced policies and protective measures.” These include a customized initial setup and a resource designed to promote understanding of artificial intelligence.

Functionally, the teen-focused Gemini closely mirrors the regular Gemini experience. This similarity extends to the inclusion of the “double-check” tool, which verifies the accuracy of Gemini’s responses by searching the internet.

Key Features and Safeguards

The teen experience prioritizes safety through specific policy adjustments.

A dedicated onboarding process ensures new users understand the platform’s capabilities and limitations.

Furthermore, an AI literacy guide is provided to help teens critically evaluate information generated by the AI.

Similarities to the Standard Gemini

Despite the added safeguards, the core functionality remains consistent.

Users will find a familiar interface and access to the same features as the standard Gemini application.

The “double-check” feature is a crucial component, enabling users to independently verify the information provided.

• It scans the web for corroborating evidence.
• This promotes responsible AI usage.
• It encourages critical thinking about AI-generated content.

Exploring the Capabilities of Gemini Models

The Gemini models represent a significant advancement in artificial intelligence, distinguished by their multimodal nature. This allows them to handle diverse tasks, encompassing speech transcription, real-time image and video captioning, and more. Numerous of these functionalities are already integrated into existing products, with Google anticipating further expansions in the near future.

It's important to acknowledge that, despite these advancements, Google hasn't resolved inherent challenges within generative AI. Issues like embedded biases and the propensity for generating inaccurate information – often referred to as hallucinations – persist. These limitations are shared by competitors, and should be considered when evaluating the use of Gemini.

Gemini Pro: Enhanced Coding and Reasoning

Google asserts that Gemini 2.0 Pro represents its most capable model to date, particularly excelling in coding and handling intricate prompts. Performance benchmarks demonstrate that 2.0 Pro surpasses its predecessor, Gemini 1.5 Pro, in areas such as programming, logical reasoning, mathematical problem-solving, and factual precision.

Within the Google Vertex AI environment, developers have the ability to customize Gemini Pro for specific applications and contexts through fine-tuning or data “grounding.” This allows the model to utilize data from external sources like Moody’s, Thomson Reuters, ZoomInfo, and MSCI, or draw information from corporate databases or Google Search instead of relying solely on its pre-existing knowledge base. Furthermore, Gemini Pro can integrate with external APIs to automate processes.

The Google AI Studio platform provides pre-built templates for crafting structured chat prompts with Pro. Developers can regulate the model’s creativity, provide illustrative examples to guide its tone and style, and adjust its safety parameters.

Gemini Flash and Flash Thinking: Efficiency and Reasoning

Gemini 2.0 Flash, capable of leveraging tools like Google Search and interacting with external APIs, demonstrates superior performance compared to some larger Gemini 1.5 models in coding and image analysis benchmarks. Designed for speed and efficiency, Flash is optimized for narrow, high-volume generative AI workloads.

Google highlights Flash’s suitability for tasks including summarization, chat applications, image and video captioning, and data extraction from extensive documents and tables. Gemini 2.0 Flash-Lite, a more compact iteration of Flash, achieves performance comparable to Gemini 1.5 Flash while maintaining the same cost and speed, according to Google.

In December, Google introduced a “thinking” version of Gemini 2.0 Flash, equipped with reasoning capabilities. This version pauses briefly to analyze a problem before providing a response, potentially enhancing the reliability of its outputs.

Gemini Nano: On-Device Processing

Gemini Nano is a streamlined version of Gemini designed to operate directly on devices, eliminating the need for data transmission to a remote server. Currently, Nano powers features on the Pixel 8 Pro, Pixel 8, Pixel 9 Pro, Pixel 9, and Samsung Galaxy S24, including Summarize in Recorder and Smart Reply in Gboard.

The Recorder application, which records and transcribes audio, now incorporates Gemini-powered summaries of conversations, interviews, presentations, and other audio content. These summaries are available even without an internet connection, and prioritize user privacy by processing data locally on the device.

Nano also enhances Gboard, Google’s keyboard, by powering Smart Reply, which suggests appropriate responses during messaging conversations.

Future Android releases will utilize Nano to identify potential scams during phone calls. The Pixel phones’ weather app leverages Gemini Nano to generate personalized weather reports. Additionally, TalkBack, Google’s accessibility service, employs Nano to create audio descriptions of objects for visually impaired users.

Gemini Ultra: Current Status

Gemini Ultra has been relatively absent from recent updates. It is not currently available within the Gemini applications, nor is it listed on Google’s Gemini API pricing page. However, this does not preclude the possibility of its future reintroduction.

Gemini Model Pricing Details

The Gemini 1.5 Pro, 1.5 Flash, 2.0 Flash, and 2.0 Flash-Lite models are accessible via the Google Gemini API. This allows developers to integrate these models into their applications and services.

A pay-as-you-go pricing structure is utilized. The following details the base costs, current as of February 225, excluding any potential add-on charges.

Pricing Breakdown

• Gemini 1.5 Pro: Pricing is tiered based on prompt length. For prompts up to 128K tokens, the cost is $1.25 per 1 million input tokens. Longer prompts, exceeding 128K tokens, are priced at $2.50 per 1 million input tokens. Output tokens are $5 per 1 million (up to 128K tokens) or $10 per 1 million (exceeding 128K tokens).
• Gemini 1.5 Flash: Input tokens are charged at 7.5 cents per 1 million (for prompts up to 128K tokens) and 15 cents per 1 million (for prompts longer than 128K tokens). Output tokens cost 30 cents per 1 million (up to 128K tokens) or 60 cents per 1 million (exceeding 128K tokens).
• Gemini 2.0 Flash: The cost for input tokens is 10 cents per 1 million. Output tokens are priced at 40 cents per 1 million. Audio input tokens are 70 cents per 1 million.
• Gemini 2.0 Flash-Lite: Input tokens are 7.5 cents per 1 million, while output tokens are 30 cents per 1 million.

Tokens represent fragmented units of data. Consider the word "fantastic," which can be broken down into tokens like "fan," "tas," and "tic."

Approximately 750,000 words are equivalent to 1 million tokens. It’s important to distinguish between input tokens – the data provided to the model – and output tokens – the data generated by the model.

Pricing for Gemini 2.0 Pro has not yet been publicly released. Furthermore, the Nano model remains in an early access phase.

Will Gemini Be Available on iPhones?

The possibility exists.

Apple has indicated ongoing discussions regarding the integration of Gemini and other external AI models into its Apple Intelligence features. During the WWDC 2024 keynote, Apple Senior Vice President Craig Federighi verified intentions to collaborate with various models, encompassing Gemini, though specifics were not disclosed.

Details Remain Scarce

Currently, concrete information regarding the implementation of Gemini on iPhones is limited.

Apple’s announcement focused on the broader strategy of leveraging third-party AI, rather than detailing a specific timeline or feature set for Gemini integration.

What We Know So Far

• Apple is exploring the use of multiple AI models.
• Gemini is among the models being considered.
• Further details will be revealed at a later date.

The confirmation of talks suggests a potential future where iPhone users could benefit from Gemini’s capabilities.

However, the extent and nature of this integration remain to be seen.

This article was initially published on February 16, 2024, and receives periodic updates.