Jeff releases small decision models for local use

The Jeff project has released model weights and code for small AI models that choose among options described in plain language and return a probability for each choice. Its published models include 0.8B and 2B parameter versions based on Qwen3.5, plus a Gemma 4 variant. Developers can run them locally through an interface compatible with Jev requests. The project reports a 22 ms decision time on an RTX PRO 6000 and 28 ms on an Apple M4 Max for its 0.8B model. It says the models work best for classification and grounding; their reasoning scores remain well below those of larger models.