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Ollama now supports Jev-style decision models

Ollama now supports decision models, based on TypeSafe's Jev API for fast, typed decisions. Decision models can now be run at no cost with low latency. Based on text, decision models answer yes-or-no questions, choices and scores about it, with a probability for every option.

Read the full story at Ollama Blog ↗

Timeline · 2 reports

  1. 2026-09-29 15:14 · r/huggingface
    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
  2. 2026-09-29 00:00 · Ollama Blog
    Ollama now supports Jev-style decision models

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  1. Trained locally: ultra-fast 0.8B/2B System 1 decision models that match Jev on benchmarks and Doom, ~30 ms per decision (open weights) — r/LocalLLaMA
  2. OpenDecider: distilling calibrated "System One" decision models from open teachers, evaluated head-to-head against Laya and TypeSafe's Jev — r/machinelearningnews
  3. LLM or JEV? Why not both? - introducing a hybrid Gemma4 approach — r/LocalLLM
  4. How long until OpenAI release their version of Jev? — r/AI_Agents
  5. More Features Are Not More Evidence: Limits of Training-Free Human Activity Recognition with Jev — arXiv cs.AI
  6. Typed Decision Models: An Early Evidence Audit and Evaluation Checklist — arXiv cs.CL
  7. Jev AI vs Logprobs vs Structured Output: We Tested TypeSafe's System One Model on Our Support Queue — DEV Community — Machine Learning
  8. Open-source Jev alternative: 5.33 ms typed decisions (choice/noul/score) on CPU and small devices. — r/ChatGPTPro

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