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What is zkSync?

zkSync emerges as the leading user-centric ZK rollup solution within the Ethereum landscape. This cutting-edge scaling technique is unparalleled in its ability to securely handle unlimited volume on Layer 2, distinguishing it from alternative approaches. Unlike optimistic rollups, zkSync enables swift and cost-effective asset transfers between the ZK rollup and Layer 1. It's worth noting that zkSync offers the most affordable transaction fees among all existing and upcoming rollups. Moreover, it includes functionalities such as meta-transactions, instant confirmations with economic finality, and economical privacy solutions. The philosophy driving zkSync's design prioritizes both simplicity and a pleasurable development experience. Developers can seamlessly incorporate payment systems and atomic swaps with minimal coding effort. Additionally, zkSync supports the development of type-safe, functional smart contracts using Zinc, a Rust-based framework, while also allowing the deployment of existing EVM codebases with slight modifications. This impressive array of features positions zkSync as a compelling option for developers who are eager to achieve both efficiency and innovation in their blockchain projects, ultimately fostering a more accessible environment for blockchain advancement.

What is Jev?

Jev is a low-latency System One Model from TypeSafe AI built for structured decision-making rather than open-ended text generation. TypeSafe describes System One Models as a new class of frontier models intended to make fast decisions that can be consumed directly by application code. Jev takes unstructured information as input and returns predefined typed outputs with probabilities and confidence scores instead of generating unrestricted natural-language strings. Its parallel sampling architecture produces outputs in a single query rather than sequentially generating one token at a time, which is designed to reduce latency and inference cost. The model is trained with Reinforcement Learning for Calibrated Decisions, which focuses on producing well-calibrated probabilities for structured System One tasks. TypeSafe positions Jev as a software-native intelligence layer for tasks including classification, routing, scoring, extraction, decision branching, and other workflows that benefit from probabilistic logic. It can also be applied to model evaluation and safety workflows by scoring, judging, verifying, guardrailing, or detecting jailbreaks in prompts, reasoning traces, and generated outputs. The company reports service response times of roughly 70 to 500 milliseconds and says this can make Jev suitable for interactive and real-time applications where traditional frontier models may introduce too much latency. Jev is designed to return consistent schemas without type errors, allowing its results to be incorporated into code without the same parsing and validation steps commonly required for free-form LLM responses. TypeSafe also highlights map-reduce style processing over large datasets as a potential use case, where the model can turn large amounts of unstructured information into structured features and insights.

Media

Media

Integrations Supported

1inch Wallet
Across Protocol
Birdeye.so
Bitget Wallet
Caldera
Chainlens
Cryptoworth
FileMarket
Holograph
Integral
Kryptos
L2BEAT
NFTScan
NOWNodes
OpenOcean
Parsec
Swoop Exchange
Symbiosis Finance
WOOFi

Integrations Supported

1inch Wallet
Across Protocol
Birdeye.so
Bitget Wallet
Caldera
Chainlens
Cryptoworth
FileMarket
Holograph
Integral
Kryptos
L2BEAT
NFTScan
NOWNodes
OpenOcean
Parsec
Swoop Exchange
Symbiosis Finance
WOOFi

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

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

Output tokens: FREE (too cheap to meter).
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Matter Labs

Date Founded

2019

Company Location

Germany

Company Website

zksync.io

Company Facts

Organization Name

TypeSafe AI

Date Founded

2024

Company Location

United States

Company Website

typesafe.ai/

Categories and Features

Categories and Features

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