# Hybrid Architecture

Liquid AI released LFM3, a family that puts text, vision, audio, omni and decision models on one shared backbone of roughly 2B parameters, with base and post-trained weights open-weight on Hugging Face and its API. The backbone mixes gated short convolutions, sliding-window attention and global attention, was pre-trained on 22T tokens, and a final 3.5T-token mid-training stage extends context to 256K. Per parameter, LFM3-1.7B matches LFM2-1.2B on short prompts across edge devices and is about 25% faster with 8K tokens in context.

Liquid AI released LFM3, a family that puts text, vision, audio, omni and decision models on one shared backbone of roughly 2B parameters, with base and post-trained weights open-weight on Hugging Face and its API. The backbone mixes gated short convolutions, sliding-window attention and global attention, was pre-trained on 22T tokens, and a final 3.5T-token mid-training stage extends context to 256K. Per parameter, LFM3-1.7B matches LFM2-1.2B on short prompts across edge devices and is about 25% faster with 8K tokens in context.

The work proposes a dual-process-inspired hybrid framework in which a TransFuser++ neural planner generates human-like trajectories in routine driving while a meta-cognitive component, using risk fields shaped by knowledge-graph reasoning, decides when to switch to a model predictive control planner; tested in CARLA on out-of-distribution scenarios of vehicles (including an ambulance) running a red light, it reduced vehicle-to-vehicle collisions from 48 to 5 out of 160 simulations, an 89% reduction.

The work proposes a dual-process-inspired hybrid framework in which a TransFuser++ neural planner generates human-like trajectories in routine driving while a meta-cognitive component, using risk fields shaped by knowledge-graph reasoning, decides when to switch to a model predictive control planner; tested in CARLA on out-of-distribution scenarios of vehicles (including an ambulance) running a red light, it reduced vehicle-to-vehicle collisions from 48 to 5 out of 160 simulations, an 89% reduction.