Ollama now supports Jev-style decision models

Ollama 0.35 added support for Jev-style decision models via TypeSafe's Jev API, exposing a new /v1/systemone endpoint that answers a set of named typed questions from a single state input at no additional cost. Three decision models ship with the release: Bespoke Labs' open-source 9B nimble, plus Together AI's experimental 4B tev1 and 0.8B tev1:0.8b. Ollama reported nimble 9B averaged 91ms per decision running locally on an M5 Max, targeting fast tasks such as ticket triage, model routing, and content or safety moderation.

Ollama now supports Jev-style decision models September 29, 2026 Ollama now supports decision models, based on TypeSafe’s Jev API https://typesafe.ai for fast, typed decisions: - No additional costs - Lower latency when run locally - Three new decision models available today via Ollama This new API is available as of Ollama 0.35 by using the new /v1/systemone endpoint. Send text as state with a set of named questions, and a model running on your machine answers them all in one request. This is great for tasks that require fast decisions, such as ticket triage, model routing, and content or safety moderation. Near-instant decisions Decision models on Ollama are fast, as requests don’t have to travel over a network. Nimble 9B averaged 91ms per decision in the Pac-Man example below when running locally on an M5 Max. That’s fast enough to make rapid decisions such as playing a game or processing content in real time: Available models Three new decision models are available to run via Ollama: - nimble https://ollama.com/library/nimble : open-source 9B parameter decision model developed by Bespoke Labs - tev1 https://ollama.com/library/tev1 : an experimental 4B decision model from Together AI - tev1:0.8b https://ollama.com/library/tev1:0.8b : an experimental 0.8B decision model from Together AI More decision models are coming soon, including models served by Ollama’s cloud. Get started To get started, first download https://ollama.com/download or upgrade to the latest version of Ollama. Next, download a decision model such as nimble : ollama pull nimble You can make a request via curl or via TypeSafe’s official Python SDK. Request curl http://localhost:11434/v1/systemone -d '{ "model": "nimble", "state": { "ticket": "I was charged twice. Please refund the extra payment." }, "questions": { "team": { "type": "choice", "instructions": "Which team should handle this ticket?", "criteria": { "billing": "Payments and refunds", "technical": "Bugs and integrations", "other": "None of the above" } }, "refund": { "type": "noul", "instructions": "Does the customer explicitly ask for a refund?" }, "urgency": { "type": "score", "instructions": "How urgent is this ticket?", "criteria": "Routine", "Soon", "Urgent" } } }' Response { "model": "nimble", "answers": { "team": { "type": "choice", "choice": "billing", "probabilities": {"billing": 0.985, "technical": 0.012, "other": 0.003}, "confidence": 0.922 }, "refund": {"type": "noul", "noul": 0.997}, "urgency": { "type": "score", "score": 0.815, "legend": {"0": "Routine", "1": "Soon", "2": "Urgent"}, "probabilities": {"0": 0.378, "1": 0.429, "2": 0.193}, "confidence": 0.046 } }, "usage": {"input tokens": 841, "output tokens": 4} } Setup uv add typesafe-sdk or: pip install typesafe-sdk export TYPESAFE BASE URL=http://localhost:11434 export TYPESAFE API KEY=ollama export TYPESAFE DEFAULT MODEL=nimble Request python from typesafe sdk import Choice, Noul, Score, TypeSafeClient ticket = "I was charged twice. Please refund the extra payment." questions = { "team": Choice instructions="Which team should handle this ticket?", criteria={ "billing": "Payments and refunds", "technical": "Bugs and integrations", "other": "None of the above", }, , "refund": Noul instructions="Does the customer explicitly ask for a refund?", , "urgency": Score instructions="How urgent is this ticket?", criteria= "Routine", "Soon", "Urgent" , , } with TypeSafeClient timeout=120 as client: result = client.system one state={"ticket": ticket}, questions=questions, print result.choices "team" .choice billing print result.nouls "refund" .noul 0.997 print result.scores "urgency" .score 0.815 What’s next This is the first of many releases to come adding decision model support to Ollama. Future updates will include: - Faster performance on Apple Silicon powered by MLX - More models specializing in different kinds of decision making