Multimodal open d1 decision models for the edge

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Multimodal open d1 decision models for the edge

LiquidAI Fernando Fernandes Neto fernandofernandes

LiquidAI Edoardo Mosca EdoardoMosca

LiquidAI Maxime Labonne mlabonne

LiquidAI Leonie Monigatti iamleonie

Today, we release two open decision models in our d1 decision model family: d1-3B and d1-omni-600M (experimental).

Best decision model under 10B on the Decision Index 0.2.1: d1-3B scores 48.57, ahead of every 4B and 9B model and of Decider 35B-A3B (47.11).

Multimodal: d1-3B supports text and images, while d1-omni-600M supports text and images or text and audio

Fast: d1-3B answers a question in 16 ms on an NVIDIA Jetson AGX Thor, 26 ms on a Jetson AGX Orin, and 50ms on a Jetson Orin Nano

How we built decision models for the edge

These open d1 decision models are built on our Liquid Foundation Models (LFMs). Unlike our generative models, decision models don’t produce tokens but answer in a single forward pass.
d1-3B and d1-omni-600M are trained from two very different backbones:

d1-3B is trained from LFM2.5-VL-3B, our latest VLM, which is decoder-only. It accepts text and images as inputs.