Gemini
Gemini is Google DeepMind’s next-generation, multimodal foundation model family (Gemini Ultra, Pro, Nano) designed for advanced reasoning, code generation, and on-device and cloud deployment across Google products and developer platforms.
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Quick Overview
Best for: Chat
What it does
LLMs software for decision-makers comparing workflow fit and alternatives.
Best fit
Chat
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Gemini
Gemini is Google DeepMind’s most capable and general multimodal AI model family, designed to understand and reason across text, code, images, audio and video. The first release, Gemini 1.0, is offered in three sizes—Ultra (largest), Pro (balanced for many tasks), and Nano (optimized for on-device use)—and is intended for use across consumer products, developer platforms, and enterprise deployments. Gemini emphasizes state-of-the-art benchmark performance, multimodal reasoning, coding capabilities, and deployment flexibility from data centers to mobile devices, while incorporating extensive safety and responsible AI practices.
Google's largest and most capable AI model, built to be multimodal and able to understand and operate across text, images, audio, video, and code. It offers a guided learning mode to help users build deep understanding through step-by-step problem solving, questions, visuals, and quizzes.
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Native multimodality
Pre-trained from the start on multiple modalities so it can seamlessly understand and reason about text, images, audio, video and code without stitching separate modality components.
Three model sizes (Ultra, Pro, Nano)
Gemini Ultra for the most complex tasks, Gemini Pro for general scaling across tasks, and Gemini Nano optimized for efficient on-device inference (e.g., Pixel 8 Pro).
State-of-the-art benchmark performance
Gemini Ultra exceeds prior state-of-the-art on 30 of 32 widely-used LLM benchmarks, outperforms humans on MMLU, and achieves top results on multimodal benchmarks like MMMU.
Advanced coding capabilities
Understands, explains and generates code in major languages (Python, Java, C++, Go); powers AlphaCode 2 for competitive programming improvements.
Scalable and efficient serving and training
Trained and served on Google’s TPU infrastructure (TPU v4 and v5e) with announcement of Cloud TPU v5p for faster training and efficient serving.
Built-in safety and evaluation
Comprehensive safety evaluations, adversarial testing, safety classifiers, filters, and external red-team reviews to identify and mitigate risks.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Enhancing Google products
Gemini Pro is being integrated into Bard, Search (SGE), Pixel features (Recorder summarization, Smart Reply), Ads, Chrome, and Duet AI to improve reasoning, latency and user experiences.
Developer and enterprise applications
Developers and enterprises can access Gemini Pro via the Gemini API in Google AI Studio or Vertex AI to prototype, customize, and deploy generative AI applications with enterprise controls.
On-device assistance
Gemini Nano enables on-device tasks on Pixel 8 Pro and via Android AICore, powering features like summarization and smarter typing suggestions with lower latency and offline capabilities.
Advanced coding and research
Used as an engine for code generation systems (AlphaCode 2) and to assist programmers with design, reasoning and implementation across programming competitions and engineering tasks.
Large-scale document understanding
Gemini’s multimodal reasoning can extract insights from hundreds of thousands of documents, aiding workflows in science, finance, and other data-intensive fields.
Integrations
Google AI Studio
Web-based developer tool to prototype and launch apps with the Gemini API.
Google Cloud Vertex AI
Managed platform for customizing Gemini with enterprise features, data control and governance.
Bard
Bard will use a fine-tuned version of Gemini Pro for upgraded reasoning and understanding.
Pixel devices (Pixel 8 Pro)
Gemini Nano powers on-device features like Recorder summarization and Smart Reply.
Search Generative Experience (SGE)
Gemini is being experimented with in Search to reduce latency and improve quality.
Android AICore
System capability enabling on-device access to Gemini Nano for Android developers.
Cloud TPU v5p
Next-generation TPU system to train and accelerate Gemini development and large-scale model training.
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Step 1: Prototype with Google AI Studio using a Gemini API key (Google AI Studio is a free, web-based developer tool).
- 2 Step 2: For managed, production-grade deployments, use Google Cloud Vertex AI to customize Gemini with enterprise security, privacy and governance features.
- 3 Step 3: Android developers can build with Gemini Nano via AICore (Android 14) and sign up for early previews; Pixel owners benefit from pre-integrated features like Recorder summarization and Smart Reply.
Support
docs
Gemini technical report and AlphaCode 2 technical report are referenced on the announcement page for technical details and evaluations.
developer platforms
Google AI Studio and Google Cloud Vertex AI are the primary platforms for accessing Gemini and provide onboarding, tools and platform-level resources.
API
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