Decision Models / Nimble
OPEN
By Bespoke Labs · Released 18 Sep 2026
A 9B decision model, LoRA-tuned from Qwen3.5-9B, with its 2,676 training examples published. One of the first two models in Ollama's decision support. Bespoke Labs followed with hosted Nimble v4 (9B) and v4-max (27B) on 13 Oct 2026.
Source: GitHub → Source: Ollama → Source: Hugging Face → Source: Nimble README →
Runs Bespoke Nimble-9B and three Laya checkpoints as players over the same 200 seeds of a headless Slay the Spire simulator, zero-shot and fine-tuned. The results are the authors' own.
A macOS app whose browser agent makes every choice, such as which element to click, as one classification by Nimble-9B running locally in Ollama. Low-confidence calls go to the person.
A Thunderbird extension that tags your email with decision models served by Ollama's /v1/systemone endpoint, such as Tev1 0.8B, Tev1 4B or Nimble, and keeps learning from the tags you add by hand.
Calls Jev, OpenAI's Decisions API, Upstage Solar Decide and local Ollama models through one interface and logs version, latency, tokens and cost. On picking the right one of 12 tools for 40 Korean and English requests, the maker measured Jev 1.13 at 40 of 40 and OpenAI Decisions at 0.90, against 0.85 for a generative model choosing directly.