Google has launched the Gemini Decisions API, powered by a new model, Gemini Decision 1 (gemini-decision-1). The Gemini Decisions API does not generate text. It scores up to 1,000 typed questions against one shared input and returns calibrated probabilities. For developers, this targets the small branching calls inside agents: routing, policy checks, tool selection and grading. Google prices it at $0.10 per 1M input tokens, with zero output tokens billed.
Gemini Decision 1 is a specialized multimodal model from Google built for closed-set decisions. It reads text, images, video, audio and PDFs in one prefill pass. Output token usage is always 0. Your code branches directly on the returned numbers.
Each request has 3 parts: a model ID, a shared input, and a map of questions. The docs define 3 question types:
Every answer carries a confidence value from 0 to 1. Google suggests routing low-confidence cases to a fallback or a human reviewer. Questions are scored in parallel and cannot see each other.
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