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id: "analysis-of-decision-model-implementations-and-benchmarks-4bb7e0"
slug: "analysis-of-decision-model-implementations-and-benchmarks-4bb7e0"
title: "Analysis of decision model implementations and benchmarks"
description: "A Habr article compares six decision-model implementations: Jev, Clef, Clef-flash, pplx-decider, Strands Decider, Laya and GLiDE."
retrieval_nugget: "A Habr article compares six decision-model implementations: Jev, Clef, Clef-flash, pplx-decider, Strands Decider, Laya and GLiDE."
observed_at: "2026-10-08"
record_date: "2026-10-08"
date_kind: "observed_at"
why_it_matters: "A Habr article compares six decision-model implementations: Jev, Clef, Clef-flash, pplx-decider, Strands Decider, Laya and GLiDE. These systems take a system state and typed questions, then return probabilities over allowed answers in a single pass rather than generating text tokens. The article describes distinct implementation choices, including frozen LLMs with trained output components, a fixe"
novelty: "notable"
verification_level: "source-linked"
signal_type: "research"
source_platform: "habr.com"
topics: []
entities: []
related_patterns: []
source_url: "https://habr.com/ru/articles/1091188?amp%3Butm_medium=rss&amp%3Butm_source=habrahabr"
source_urls: ["https://habr.com/ru/articles/1091188?amp%3Butm_medium=rss&amp%3Butm_source=habrahabr"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "signal:analysis-of-decision-model-implementations-and-benchmarks-4bb7e0"
status: "published"
visuals: []
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
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---

# Analysis of decision model implementations and benchmarks

## Retrieval answer

A Habr article compares six decision-model implementations: Jev, Clef, Clef-flash, pplx-decider, Strands Decider, Laya and GLiDE.

A Habr article compares six decision-model implementations: Jev, Clef, Clef-flash, pplx-decider, Strands Decider, Laya and GLiDE. These systems take a system state and typed questions, then return probabilities over allowed answers in a single pass rather than generating text tokens. The article describes distinct implementation choices, including frozen LLMs with trained output components, a fixed decision head, a pointer mechanism and a masked encoder. It also reports non-uniform benchmark results: Clef scores above Jev on BANKING77, while Jev scores above Clef on When2Call. The article is a technical comparison, not evidence that any one model is best for all agent workloads. Source: https://habr.com/ru/articles/1091188?amp%3Butm_medium=rss&amp%3Butm_source=habrahabr

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

## Continue in the graph

Next records for an agent, linked to their Markdown twins. Replace `.md` with `.json` for structured fields, including `next_reads`.

- collection: [Raw Signals](https://newruntime.com/signals.json): Open every source-linked raw signal.
- collection: [Source Ledger](https://newruntime.com/source-ledger.json): Inspect the public source evidence graph.
- whole graph: [discovery graph](https://newruntime.com/discovery-graph.json) (typed nodes and edges) and [site index](https://newruntime.com/site-index.md)