Entity trail

jevals

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Corpus findings

2026-09-21 / saas-disruption-researcherCROSS-CATEGORY: Small Typed Decision Models Showed Up in Evals, Moderation and Local Inference All in One WeekendThree separate projects hit Hacker News within 48 hours attacking the same assumption, that a frontier model must be the thing making a yes/no call: jevals for agent evaluation gating, Kev as an open-weights decision-model family on Qwen3.5 (0.8B to 9B, 0.852 accuracy against TypeSafe Jev's 0.857), and a laya-coreml setup running a multilingual decision model fully offline on a Mac M4 at a 560MB physical footprint. Arize's September 18 analysis of Jev put the tradeoff at 68% accuracy for $0.0004 and 0.4 seconds per case versus Opus 5 at 73% for $0.18 and 38 seconds, and noted what you lose is the explanation. Any SaaS whose cost line is frontier-model classification should be re-pricing this week.
2026-09-21 / saas-disruption-researcherjevals Replaces LLM Judges With Decision Models and Publishes the Bill: $2.60 Per Sample Down to $0.03Openlayer released jevals, a week-old alpha Python library that runs every eval for a trace in one request against a decision model instead of a frontier LLM. Its published comparison puts Ragas at 6 to 11 requests per sample, $2.60 per sample and 22 to 35 seconds for 20 samples, against jevals on Jev at one request, $0.03 per sample and 0.8 seconds, with p50 latency of 244ms. Local backends (Kev, Laya) drop the cost to zero at 1 to 6 seconds per sample. The eval-platform category has spent two years billing for frontier tokens it may no longer need to spend.

Graph relationships

COMPETES WITH
Ragas
jevals reduces cost from $2.60 per sample with Ragas to $0.03 with Jev
Source finding
BUILT BY
Openlayer
Openlayer released jevals as a Python evaluation library
Source finding
COMPETES WITH
Opus 5
jevals replaces frontier LLM judges with cheaper decision models compared to Opus 5
Source finding
USES
Jev
jevals can use Jev as a backend for decision model evaluation
Source finding

Source trail

Synthesis of jaredpalmer/kev and openlayer-ai/jevals on GitHub, the laya-coreml gist (all HN 2026-09-20/21) and Arize AI's Jev analysis (2026-09-18)openlayer-ai/jevals on GitHub (primary; vendor-run benchmark numbers, surfaced on HN 2026-09-20)

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