Liquid AI released d1-ultra on October 15, a multimodal decision model that takes text, images or both and returns calibrated probabilities for yes/no, multiple-choice and score questions in a single forward pass, without generating output tokens. It has a 32,768-token context window and is billed on input only, at $0.042 per million input tokens.

Liquid pitches it at work such as spotting defects against a product specification, reviewing damage claims from customer photos and checking whether product images match their listings. The company says the model leads its 112-test suite and scores 65 on the Artificial Analysis Decision Index, ahead of TypeSafe's Jev at 58 and Microsoft-Decision-1 at 54 — all vendor-reported figures on vendor-chosen tasks.

The model is available through Liquid's API, with Vercel AI Gateway and OpenRouter support listed. The decision-model category keeps filling in — Microsoft, Cloudflare, AWS and OpenAI have all shipped versions since September — but an early independent trading-replay test ranked d1-ultra near the bottom of its field, a reminder that a confident probability is only useful if it stays calibrated on the customer's own decisions.