Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Gemini Decision 1 is a specialized AI model from Google designed to evaluate information and produce structured decisions instead of generating natural language responses. The model enables developers to ask specific questions about provided content and receive probabilistic answers that can guide automated processes. It supports several decision formats, including yes-or-no classifications, selections from predefined options, and scores based on established criteria. Each evaluation can include confidence measurements and probability distributions to help applications interpret the model's predictions. Gemini Decision 1 offers a context window of approximately 262,144 tokens, allowing it to examine lengthy documents and substantial amounts of contextual data. Applications can use the model to classify incoming requests, prioritize tasks, route information, and assess whether content meets specified requirements. Its structured outputs are particularly useful for AI agents that need to select actions or evaluate conditions within automated workflows. Developers can access the model through supported API services, including Google's Gemini API ecosystem and Vercel AI Gateway. By focusing on decision-oriented inference rather than open-ended text generation, Gemini Decision 1 provides a way to incorporate AI-powered classification and evaluation into software applications.
Description
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.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Gemini
Yes
Gemini platform
Yes
Google AI Studio
Yes
Gemini Enterprise
No
Google Cloud Platform
Yes
Mimasa AI
No
Python
No
Integrations
Gemini
Yes
Gemini platform
Yes
Google AI Studio
Yes
Gemini Enterprise
Yes
Google Cloud Platform
No
Mimasa AI
Yes
Python
Yes
Pricing Details
$0.10 per 1M tokens (input)
$0.10 per 1 million tokens (input), no charge for output tokens
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
aistudio.google.com/docs/models/gemini-decision-1
Vendor Details
Company Name
Founded
1998
Country
United States
Website
blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/