Ollama 0.35 支持 Jev 风格决策模型，新增 /v1/systemone 接口
Ollama now supports Jev-style decision models · Ollama Blog
Ollama 0.35 起支持基于 TypeSafe Jev API 的决策模型，通过新的 /v1/systemone 接口把文本作为状态并附带一组命名问题，本地模型可在一次请求中全部作答。官方称该方式无额外成本、本地运行延迟更低，适合工单分流、模型路由和内容或安全审核等需要快速决策的任务。首批上线三个模型：Bespoke Labs 开发的 9B 开源决策模型 nimble，以及 Together AI 的两个实验性决策模型 tev1 和 tev1:0.8b；本地在 M5 Max 上运行 nimble 9B 时，Pac-Man 示例中平均每次决策 91ms。可通过 curl 或 TypeSafe 官方 Python SDK 发起请求，后续将加入 Apple Silicon 上基于 MLX 的加速和更多决策模型。
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September 29, 2026
Ollama now supports decision models, based on TypeSafe’s Jev API 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: open-source 9B parameter decision model developed by Bespoke Labs; tev1: an experimental 4B decision model from Together AI; 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.
You can make a request via curl or via TypeSafe’s official Python SDK.
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