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MMR OFFICIAL@MR_0FFICIALL
ๆบ่ฝไฝ่ชๅจๅJEV
๐๐ฒ๐ ๐๐ ๐ก๐ผ๐ ๐๐ถ๐๐ฒ ๐ผ๐ป ๐.๐๐ ๐๐ฃ๐: ๐ ๐ก๐ฒ๐ ๐ช๐ฎ๐ ๐ง๐ผ ๐ ๐ฎ๐ธ๐ฒ ๐ฆ๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ ๐๐ฒ๐ฐ๐ถ๐๐ถ๐ผ๐ป๐ โก
๐๐ฒ๐ ๐๐ ๐ก๐ผ๐ ๐๐ถ๐๐ฒ ๐ผ๐ป ๐.๐๐ ๐๐ฃ๐: ๐ ๐ก๐ฒ๐ ๐ช๐ฎ๐ ๐ง๐ผ ๐ ๐ฎ๐ธ๐ฒ ๐ฆ๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ ๐๐ฒ๐ฐ๐ถ๐๐ถ๐ผ๐ป๐ โก
Most AI APIs are designed to generate something.
Text. Code. JSON. A response.
Jev takes a different approach.
From @typesafeai, Jev is a System One model designed specifically for structured decisions inside software.
Instead of asking it to generate text and then parsing the result, developers provide:
๐น App state โ the information the system needs
๐น A typed question โ what decision needs to be made
๐น A typed result โ the decision, probability and confidence
No JSON prompting.
No fragile output parsing.
Just a structured decision that software can use directly.
๐ง What Can Jev Decide?
Jev evaluates three question types in parallel:
Choice โ Select between predefined options.
Score โ Produce a structured numerical assessment.
Noul โ Make a structured binary-style decision.
That makes the model less about generating content and more about becoming a decision layer inside an application.
โก Built For Fast Decisions
According to the announcement, Jev responds in roughly 70โ500ms and costs $0.042 per million input tokens, with output tokens free.
That pricing and latency profile makes the model particularly interesting for workloads where thousands of small decisions can happen continuously.
Think:
๐น Ticket routing
๐น Content moderation
๐น Risk scoring
๐น Agent branching
๐น Automated workflow decisions
๐น Classification inside software
Instead of building a pipeline around:
Prompt โ Generated JSON โ Parser โ Validation โ Application
the idea is closer to:
App State โ Typed Question โ Typed Decision
That is a meaningful architectural difference.
๐ Now Available Through https://t.co/9CKQIEP2Jz
Jev is now available through the https://t.co/9CKQIEP2Jz API using:
Jev-1.13.0
Jev-Latest
For developers, this adds another specialized model to the https://t.co/9CKQIEP2Jz ecosystemโone designed not primarily to talk, but to help software decide.
๐ Try it through https://t.co/9CKQIEP2Jz: https://t.co/IE5evqOJKL
๐ Learn more: https://t.co/7bQibRC3KN
The interesting part of AI infrastructure is increasingly not just how well models generate.
It's how cleanly models can plug into software and perform a specific job.
#TRONEcoStar @justinsuntron @BAI_AGI
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