Google launches Gemini Decisions API with Gemini Decision 1 model
The pricing shift matters most: charging only for input tokens inverts the usual cost model and makes high-volume evaluation pipelines dramatically cheaper than running a general model like Flash-Lite. Teams building data labelling, content moderation, rubric-based grading or model-eval loops can replace token-heavy generation with a single scoring pass over up to 1,000 questions. The low calibration error claim is what evaluation engineers should verify first, since calibrated confidence is the difference between a useful judge and a noisy one.
