Liquid AI open-sources decision models that answer without writing text

Liquid AI has released two open-weight models that produce no text. Instead, they answer classification-style questions in a single forward pass.

• d1-3B: built on LFM2.5-VL-3B, it takes text and images. Liquid reports a score of 48.57 on its Decision Index, ahead of the much larger Decider 35B-A3B at 47.11, and an average of 82.9 across seven public datasets. It answers in 16 milliseconds on an NVIDIA Jetson AGX Thor and 50 milliseconds on an Orin Nano.
• d1-omni-600M: experimental, built on a small encoder with vision and audio added. It averages 78.4, with no published speed figures.

All the benchmarks are Liquid's own and haven't been replicated.

Why it matters

Earlier this month Cloudflare launched Clef, a "decision model" that returns probabilities instead of words. A second company now ships the idea as open weights, small enough for robots and edge devices. That looks less like a one-off and more like a new kind of model.