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Average Ratings 0 Ratings
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.
Description
Mercury 2.5 represents the pinnacle of production models from Inception, demonstrating a remarkable enhancement in quality compared to its predecessor, Mercury 2, all while upholding an impressive low-latency serving profile. It stands out as the most advanced diffusion language model currently available and is touted by Inception as the largest diffusion LLM ever developed. With a 40% boost in intelligence over Mercury 2, its performance aligns closely with that of cost-efficient frontier models like GPT-5.6 Luna (Low), Gemini 3.5 Flash-Lite, and Claude Haiku 4.5. The model boasts a generation speed of 1,107 tokens per second on commonly accessible NVIDIA GPUs and accommodates a generous 260K-token context window. Among its features are adjustable reasoning capabilities, simultaneous tool calls, and JSON that aligns with schemas. Specifically engineered for latency-sensitive tasks, it is well-suited for scenarios involving numerous model calls during a single interaction. In applications such as search agents and RAG pipelines, Mercury 2.5 excels in functions like planning, query rewriting, re-ranking, fact structuring, source summarization, and answer verification, all while ensuring rapid response times, making it an essential tool for developers seeking efficiency in their workflows.
API Access
Has API
API Access
Has API
Integrations
JSON
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).
Output tokens: FREE (too cheap to meter).
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
TypeSafe AI
Founded
2024
Country
United States
Website
typesafe.ai/
Vendor Details
Company Name
Inception
Country
United States
Website
www.inceptionlabs.ai/blog/introducing-mercury-2-5