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Faster model, slower chatbot. What we learned from testing Jev

This story is from 2026-10-02. It is preserved in the archive; the latest stories are on the live feed.

Originally published on the WebSpeaker blog . In short: We tested Jev, a new model for rapid decisions, as a way to speed up WebSpeaker. Jev made decisions quickly and slightly more accurately than the model we use today. Yet in every variant we tested, visitors waited longer for an answer. We did…

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  1. 2026-10-02 11:19 · DEV Community — AI
    Faster model, slower chatbot. What we learned from testing Jev

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  1. Cloudflare debuts open-weight multimodal decision models Clef and Clef-flash, claiming they are smarter and faster than Jev, based on Qwen3.8-27B and Qwen3.5-9B (Brandon Vigliarolo/The Register) — Techmeme
  2. I rebuilt a Jev-style classifier on Qwen3.5-4B: shared-prefix tree, open weights, fine-tunable, ~140 ms on one H100 — r/learnmachinelearning
  3. Mica v0.1 4B: open Jev-style decision model (yes/no, choice, score) that runs on an 8 GB GPU — trained for under $30 of GPU time — r/huggingface
  4. Amazon releases its own Jev clone as decision models flood the web — TechCrunch AI
  5. OpenAI answers TypeSafe's Jev with a Decision API built on Luna — The New Stack AI
  6. NIRNAY: 450M decision model beats Jev on Banking77, runs on CPU — r/machinelearningnews
  7. Vev: Jev-like decision models with vision — 4B/9B, local inference, open weights — r/LocalLLM
  8. New frontier AI models, TypeSafe’s Jev AI, & NASA’s IBM collab — Mixture of Experts (IBM)

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