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Liquid AI

Liquid d1

Liquid d1 models score possible answers to a question. The open d1-3B and experimental d1-omni-600M releases bring decision models to local text, image and audio workloads.

Released 7 October 20261 min readLarge Language ModelsLast updated:

Editorial illustration of Liquid d1

Key facts

7 Oct 2026
Open release
Text and images
d1-3B
Experimental
d1-omni-600M
LFM1.0
Licence

Liquid d1 models score possible answers to a question. The open d1-3B and experimental d1-omni-600M releases bring decision models to local text, image and audio workloads.

Liquid d1 is a family of AI models that assigns probabilities to supplied answers. A developer can ask a question about a document or camera image, supply the allowed choices and receive a score for each. This suits tasks such as classifying a request or checking whether an object is visible.

Liquid AI released downloadable d1-3B and d1-omni-600M weights on 7 October 2026. The company had introduced the hosted d1 service with vision support on 5 October. The downloadable models and the hosted service have separate capabilities and access routes.

Two sizes handle different inputs

The d1-3B model accepts text and images. It is built for running on local computers and edge devices, which process data near a camera or other sensor.

The smaller d1-omni-600M checkpoint is experimental. It accepts text with an image or text with audio. Its model card explains the supported input combinations and how to run them.

Model Inputs Release status
d1-3B Text and images Downloadable weights
d1-omni-600M Text with images or audio Experimental downloadable weights

The output is a decision score

d1 evaluates answer choices in one forward pass through the model. Its output is useful when software needs a bounded decision, such as selecting a category. The quality of the decision depends on the question, answer choices and input.

Both model cards specify the LFM1.0 licence. Teams distributing or using the weights commercially should read that licence and test accuracy on their own inputs. Liquid’s published speed results describe its named hardware and test conditions.