From the source
With last week's experimental release , d1 became the first model to rival Jev on text decisions, and it is now the first to extend these capabilities to images.
You can try it today at console.liquid.ai and in the d1 Playground .
We tested d1 against GPT-6.1 Sol and Claude Opus 5.5 on six real applications, from filtering support tickets to inspecting circuit boards. d1 matches or beats GPT-6.1 Sol on four of them.
It costs 19x to 200x less than both models and answers significantly faster on every task.
How the d1 decision model works Decision models answer questions about a situation with a probability for each possible answer.
The d1 decision model takes unstructured data (e.g., text, images, or both) and one or more questions as input, reads them in one forward pass, and returns the probabilities, without generating any tokens.
A text decision takes 200 to 300 ms, fast enough for real-time applications. d1 answers three types of questions: Noul : a yes/no question, answered with a probability between 0 and 1.
Choice : pick one label among many, answered with a probability per label.
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