Google launches Gemini Decisions API and Decision 1 model

Google has released Gemini Decision 1, a decision model API that supports yes/no, choice and rubric-scoring questions, joining Jev and OpenAI in the decision model category. It is priced at 10 cents per million input tokens with free output, and unlike Jev's text-only input it accepts text, images, audio, video and PDFs. In a test on a robot video, Gemini returned probabilities such as 0.9234 for robot and 0.0498 for dragon instead of the 1.0 or 0.0 that Jev and OpenAI return.

Google launched the Gemini Decisions API, powered by a new model called Gemini Decision 1 (gemini-decision-1), which does not generate text but scores up to 1,000 typed questions against one shared input and returns calibrated probabilities. It reads text, images, audio, video and PDFs in a single prefill pass, supports yes/no, choice and score question types, and is priced at $0.10 per 1M input tokens with zero output tokens billed. Google reports a 262,144-token context, 150-250 ms end-to-end latency, and a top-1 ECE of 0.0250, about half that of TypeSafe Jev 1.14, though it trails Jev on the When2Call benchmark (79.9% vs 82.0%) and costs more per token ($0.10 vs $0.042).

Google DeepMind introduced the Gemini Decisions API, built for closed-ended decisions such as yes/no questions, multiple choice, and scale-based ratings, with the underlying Gemini Decision 1 model processing up to 1,000 independent questions in a single pass across text, images, audio, video, and PDFs. It returns probabilities with confidence values in 150 to 250 milliseconds and costs $0.10 per million input tokens with no output-token charge, which Google says is about five times cheaper than Gemini 3.5 Flash-Lite. The API is available now through Google AI Studio, with integrations for OpenRouter, LangChain, and Vercel rolling out, and Google says it already uses it internally for model routing in Gemini Notebook, design prototyping in Stitch, and safety checks in Google Search.

Google introduced the Gemini Decisions API, powered by the new Gemini Decision 1 model (gemini-decision-1) and available through the Gemini API in Google AI Studio. A single multimodal input of up to 256K tokens can be checked against up to 1,000 yes/no, multiple-choice and rubric-scoring questions in one forward pass, returning probabilities and confidence scores at 150-250 ms end-to-end latency for $0.10 per 1M input tokens with no output-token charges. Google says the model leads its benchmark suite with the lowest calibration error and is nearly 5x cheaper than Gemini 3.5 Flash-Lite with the Interactions API; internal uses include model routing in Gemini Notebook, wireframe generation in Stitch and adversarial-content checks for MCP tools in Search.