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JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models offer fast probabilistic predictions over finite fields, but require those fields to be specified…

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  1. 2026-10-02 04:00 · arXiv cs.AI
    JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

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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. OpenAI's Jev clone could help the frontier lab stop its swarming agents — TechCrunch AI

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