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Liquid AI launches d1 decision model for structured tasks with zero output tokens

Liquid AI released d1, a decision model designed for structured choices like classification, ticket routing, and moderation. Unlike text-generating models, d1 returns calibrated probabilities across predefined outcomes in a single API call, with no generated tokens billed. It supports three primitives—Noul (yes/no with probability), Choice (top pick from a set), and Score (ordered rubric…

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Key points

  • d1 returns typed decisions with calibrated probabilities and zero output tokens, billed only for input
  • Supports three primitives: Noul (yes/no), Choice (top pick), and Score (ordered ratings) in one call
  • Deployable now via Liquid’s API as **d1:free**; no self-hosted weights or training options

The model is available today via Liquid’s hosted API under d1:free, with no self-hosting options. Liquid’s migration guide advises using d1 for tasks with fixed answer sets (e.g., spam detection, urgency triage) and reserving LLMs for generation or multi-step reasoning. A demo shows d1 powering a real-time road-decision game, outperforming a competitor model in consistency. The company highlights benefits like predictable latency, no schema errors, and reduced round trips compared to LLMs.

Model page: d1 →

Full story from MarkTechPost · by Asif RazzaqOpen source ↗

Liquid AI Releases d1: A Decision Model That Returns Calibrated Probabilities With Zero Output Tokens

MarkTechPost · 29 September 2026

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This text was published by MarkTechPost and written by Asif Razzaq. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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