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

Mica v0.1 4B is an open Jev-style decision model designed for agent loops, capable of handling yes/no, choice, and score decisions. It runs on an 8 GB GPU and was trained for under $30 of GPU time. The model is based on Qwen3.5-4B with a rank-16 LoRA applied across all 32 layers, including attention and Gated DeltaNet, resulting in a Qwen3.5-4B-shaped checkpoint. The developer is seeking feedback on its performance, particularly in ambiguous "act or ask" scenarios.

Unlike many larger models, Mica v0.1 4B is notable for its low training cost of under $30 and its ability to run on an 8 GB GPU, making it accessible for smaller-scale agent loop applications.