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Jev structured output decision models launch
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Jev, a structured output decision model, has sparked a wave of open-source implementations and tooling across multiple platforms. Developers are building Jev-inspired alternatives, wrappers, and benchmarks, with reported performance gains of 13.6x speed and 2.7x cost reduction versus GPT Luna 6.
- Jev 1.13 released; described as a new category of 'system one' decision models for typed outputs
- Multiple OSS alternatives launched: Eikos, Newt (Swift/Apple), Valen (multimodal), Vons (browser-based)
- Jev achieves 13.6x faster inference and 2.7x cheaper cost than GPT Luna 6
- JevBench created as reproducible benchmark for typed decision models
- Rust crate (Jev-rs) and serving tools (Jev-serve) enable LLM-to-Jev conversion for qwen3.8 and other models
[HN]hacker news20
Eikos - OSS Jev-like model
Show HN: Newt – A Swift Package for Jev-Style Decisions on Apple Core AI
Show HN: A local alternative to Jev – 94% on Banking77
Turning GLM-5.3-Flash into a Jev-like decision model
A single function Jev-like wrapper for LLMs, including vision models
Show HN: Vons – Jev-inspired local decisions for AI agents, in the browser
Valen: A multimodal decision model inspired by Jev
What Is RLCD? The Secret Behind Jev
Show HN: Chatlo – an iOS-native AI agent, now with Jev
Jev deserves hype but not the type its getting
Jev vs. LLMs on 770 "Am I the Asshole?" posts
Jev is 13.6x faster, 2.7x cheaper than GPT Luna 6
Show HN: Open Code for Jev
Show HN: I Built a GIF Decider with Jev
Jev-rs: a Rust crate to turn a LLM to serve jev
Jev-serve: Run latest qwen3.8, all LLM models, mlx-supported
Trained KV cache bank turns any LLM into Jev like Model
The Jagged Frontier of Jev 1.13
Show HN: JevBench, a reproducible benchmark for typed decision models
I made an LLM using 521 Jev models