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Jev vs Local Models: Where Japanese Intent Routing Stands After 1,000 Utterances

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

๐Ÿ“ Originally published (in Japanese) at forge.workstyle.tech . The router that decides "which process to assign this phrase to" is crucial for the usability of an assistant. There are methods where the model generates text and classifies it every time, and others where a specialized model is usedโ€ฆ

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  1. 2026-10-02 02:24 ยท DEV Community โ€” AI
    Jev vs Local Models: Where Japanese Intent Routing Stands After 1,000 Utterances

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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) โ€” Techmeme
  2. I rebuilt a Jev-style classifier on Qwen3.5-4B: shared-prefix tree, open weights, fine-tunable, ~140 ms on one H100 โ€” r/learnmachinelearning
  3. Mica v0.1 4B: open Jev-style decision model (yes/no, choice, score) that runs on an 8 GB GPU โ€” trained for under $30 of GPU time โ€” r/huggingface
  4. Amazon releases its own Jev clone as decision models flood the web โ€” TechCrunch AI
  5. OpenAI answers TypeSafe's Jev with a Decision API built on Luna โ€” The New Stack AI
  6. NIRNAY: 450M decision model beats Jev on Banking77, runs on CPU โ€” r/machinelearningnews
  7. Vev: Jev-like decision models with vision โ€” 4B/9B, local inference, open weights โ€” r/LocalLLM
  8. OpenAI's Jev clone could help the frontier lab stop its swarming agents โ€” TechCrunch AI

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