Liquid AI Open-Sources d1-3B and d1-omni-600M: Multimodal Edge Decision Models With Zero Output Tokens

Liquid AI has released two open-weight models — d1-3B and d1-omni-600M — under its new 'd1' decision model family, notable for producing zero output tokens and operating as pure decision/classification engines rather than generative models. The d1-omni-600M is explicitly designed for edge deployment, while the 3B variant handles richer multimodal inputs. This architecture is a significant departure from standard LLM paradigms and is purpose-built for latency-critical, resource-constrained inference scenarios such as robotics, embedded systems, and real-time classification pipelines. Developers building non-generative AI pipelines or needing deterministic classification on edge hardware now have open-weight multimodal options without the overhead of token generation. The models are available on Hugging Face with accompanying documentation from Liquid AI's blog.