microsoft/FrogNano-4B-2609 · Hugging Face

FrogNano-4B-2609 is a 4B agentic model from Microsoft, derived from Qwen/Qwen3.5-4B. It features a 32-layer hybrid Gated DeltaNet and gated-attention architecture. FrogNano undergoes additional text-only post-training focused on repository-level software engineering, using reinforcement learning on 1,500 synthetic SWE task environments generated by TaskPilot. It utilizes the five-tool Leaf harness and executable test-based rewards for multi-turn coding trajectories, aiming to improve repository navigation, debugging, code editing, test execution, and patch generation.

Unlike approaches based on behavioral distillation, FrogNano does not train on stronger-model solution trajectories, actions, reasoning traces, or patch targets.