NEWS · MODELS · #1687
Open multimodal decision models d1-3B and d1-omni-600M released for edge inference
The team released two open-weight decision models, d1-3B and experimental d1-omni-600M, built on their Liquid Foundation Models. d1-3B (decoder-only) supports text+images, scores 48.57 on Decision Index v0.2.1 (best under 10B) and runs in 16–50 ms on NVIDIA Jetson devices; d1-omni-600M (encoder-based) supports text+image or text+audio, is an early research release, and both models (and demos) are available on Hugging Face.
KEY POINTS
- The team released two open-weight decision models, d1-3B and experimental d1-omni-600M, built on their Liquid Foundation Models.
- d1-3B (decoder-only) supports text+images, scores 48.57 on Decision Index v0.2.1 (best under 10B) and runs in 16–50 ms on NVIDIA Jetson devices; d1-omni-600M (encoder-based) supports text+image or text+audio, is an early research release, and both models (and demos) are available on Hugging Face.
- This matters because it provides open, high-quality, low-latency multimodal decision models optimized for edge devices, lowering deployment cost and enabling structured inference where latency and footprint are critical.
WHY IT MATTERS
This matters because it provides open, high-quality, low-latency multimodal decision models optimized for edge devices, lowering deployment cost and enabling structured inference where latency and footprint are critical.