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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

Jev is TypeSafe AI’s first public System One Model, a class of AI designed to make fast, structured decisions that software can consume directly. Instead of generating arbitrary strings like a traditional large language model, Jev produces predefined type-safe values accompanied by calibrated probabilities and confidence estimates. Its architecture generates outputs in parallel rather than autoregressively producing one token at a time, allowing the model to prioritize speed and computational efficiency. TypeSafe trains Jev using Reinforcement Learning for Calibrated Decisions, an approach intended to optimize for accurate uncertainty estimates and consistent structured outputs. The model can be embedded into conventional software as an intelligent decision layer for classification, scoring, routing, extraction, branching, and other tasks where hand-written rules would be too rigid. Jev can also be used to judge, verify, guardrail, or detect problematic behavior in outputs from other AI systems. TypeSafe reports typical end-to-end response times between 70 and 500 milliseconds and positions the model for applications where low latency is important. The company also emphasizes schema guarantees, meaning Jev’s outputs are constrained to the structures defined by the application rather than requiring developers to parse and validate unrestricted generated text. Jev is aimed at developers and organizations building automation, real-time software, large-scale data workflows, and production systems that require dependable structured AI decisions.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Gemini Yes 
Gemini platform Yes 
Google AI Studio Yes 
Google Cloud Platform Yes 

Integrations

Gemini No 
Gemini platform No 
Google AI Studio No 
Google Cloud Platform No 

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

Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).

Output tokens: FREE (too cheap to meter).
Free Trial No 
Free Version 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 

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) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

aistudio.google.com/docs/models/gemini-decision-1

Vendor Details

Company Name

TypeSafe AI

Founded

2024

Country

United States

Website

typesafe.ai/

Product Features

Product Features

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