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Decision Model Leaderboard
Cloudflare's live leaderboard for decision models on the Decision Index suite, with Clef, Clef-flash, Jev, Kev-9B and Laya plotted by score and latency. Cloudflare built and ran it, so treat the ranking as vendor-run.
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Introducing Clef: our open-source decision models, and new RL fine-tuning platform
Cloudflare's launch post for Clef and Clef-flash, two decision models on Workers AI that accept the Jev request format and open weights under Apache 2.0. It covers the architecture, Cloudflare's own benchmark tables against Jev, Kev and Laya, and a new reinforcement learning service.
Michelle Chen (@michellechen)140k viewsOpenIntroducing Clef: our open-source decision models, and new RL fine-tuning platform on blog.cloudflare.comArticleSupport inbox triage
[AINews] Jev: a System One Model that only decides/classifies/routes/scores
AI News daily roundup leading with the Jev launch, summarising RLCD and TypeSafe's 20-200x speed and 40-400x cost claims. Its recap of reactions notes posters using Jev as a structured classifier, judge and routing policy where text generation is unnecessary.
Jev means structured output is interesting again
Argues Jev's speed comes mainly from constrained single-token generation and aggressive prefill, techniques reproducible with existing LLMs, rather than a new architecture. Still treats very fast structured output as a new primitive, while doubting Jev matches frontier models on raw intelligence.
ArticleZaious/jev-capability-atlas
An independent, evidence-based map of where Jev's calibrated-decision claim holds up and where it breaks down, built from real API-call receipts rather than a leaderboard.
Articlewillkelly/jev-evaluation
An adversarial evaluation of Jev with nine experiments and 28 predictions fixed before any data was collected. One run covered 123,805 requests over 138 minutes for $12.69, with five failures, plus a 13-rule prompting guide.
Article
WindTunnel: the WebMCP benchmark
A 49-task, 8-site browser-agent benchmark. Jev paired with a small model for argument generation solved 100% of tasks at far lower cost than screenshot-based computer use, and adding WebMCP tool exposure roughly doubled Jev's own solve rate from 25 to 49 tasks.
idan levin (@0xidanlevin)OpenWindTunnel: the WebMCP benchmark on webmcp.com239k viewsSolve rate 25/49 to 49/49Cost vs Astra 112x lower
