Can AI Read Long Texts and Answer '1,000 Multiple-Choice Questions' in 0.2 Seconds? The Secret Behind Google's Gemini Decisions API

What happens if we throw a long report or customer review at the artificial intelligence (AI) chatbots we normally use and ask, “Based on this, summarize the core points and judge whether it’s positive or negative”? Like a skilled writer carefully pressing down their pen, the AI writes out answers one character at a time, sequentially generating tokens (the basic unit by which AI reads and writes sentences). We have to wait several seconds for the result, and picking out the “short-form conclusion” we truly wanted from long, complex answers was entirely up to us.

However, there are far more moments in the world that require clear “decisions” and “choices” rather than verbose descriptive text. Business environments require meticulously checking whether thousands of customer reviews constitute refund grounds, if dangerous toxic clauses are hidden among contract provisions, or if products in videos comply with regulations. Google’s newly unveiled AI tool completely upends this dilemma [Source] [Source]. Google’s newly introduced Gemini Decisions API (a developer tool that evaluates numerous structured questions at once for text and multimedia inputs) is an entirely new type of AI model that dispenses with long-form writing and outputs ultra-fast “decisions” exclusively [Source] [Source].

Why Does This Matter?

If you handle processing large volumes of documents or analyzing customer feedback via smartphone or PC in your daily life, you have likely felt fatigued by the verbose answers produced by AI. While traditional generative AI excels at writing stories or coding, asking it to “Answer with O/X whether each of these 1,000 product reviews is eligible for a refund” consumed massive amounts of time and cost as it generated tokens one by one.

Gemini Decisions API has smashed through this wall of inefficiency. This tool operates based on Google’s latest GeminiDecision1 (Google’s next-generation AI model specialized in decision-making and structured question evaluation) model [Source] [Source]. When a user inputs various forms of data such as text, images, audio, video, or PDFs and poses up to 1,000 questions, the AI processes them simultaneously in a single pass (a method of scanning and processing data all at once) [Source] [Source].

It also delivers a massive shock in terms of speed and economics. The time required to process 1,000 complex decisions is a mere 150 to 250 milliseconds (ultra-short time of 0.15 to 0.25 seconds) [Source]. Pricing is similarly set at 10 cents per million input tokens, with zero charges for output tokens [Source]. Because there is no need to output lengthy results, the cost structure that enterprises must bear when utilizing AI has been radically lightened.

Easy to Understand: From AI Writer to “Ultra-Fast Multiple-Choice Exam Grader”

To intuitively understand how this technology works, let’s look at two analogies.

The first analogy is the difference between a novelist and an O/X exam grader. If a traditional Large Language Model (LLM, an artificial intelligence that learns massive data to speak sentences like a human) is a writer participating in a composition contest, it excels at crafting emotional, lengthy texts character by character on A4 paper when given a prompt. In contrast, the newly unveiled GeminiDecision1 model is like a machine that instantly grades a 1,000-question national civil service multiple-choice exam. Instead of elaborately creating long prose, it accurately scans the input data (text, video, etc.) and immediately marks each question with “Yes/No”, “True/False”, or precise numerical values and confidence levels according to multiple-choice and score rubrics (scoring criteria tables).

In short: Instead of having AI read a long letter and ask for its thoughts, you throw 1,000 checklists at it—such as “Is this letter sad? (Yes/No)”, “What is the author’s anger level from 0 to 10?”, “What are the main topics mentioned among A, B, and C?”—and it completes the checklist perfectly in just 0.2 seconds.

The second analogy is smartphone facial recognition unlock. When we look at the camera, the smartphone meticulously analyzes the entire screen and makes a single massive decision of “True” or “False” to the single question, “Is this person the owner?” The Gemini Decisions API extends this principle across all kinds of complex digital assets like documents, audio, video, and images, serving as a magical checklist engine that executes thousands of judgment items simultaneously.

Imagine this. A large shopping mall operations team receives tens of thousands of customer review videos and call center recording files every day. In the past, all this data had to be summarized in block text by AI or manually monitored by people. Now, through the Decisions API, up to 1,000 questions—such as refund eligibility, customer complaint severity scores, and complaint category classifications—can be tagged at once and results received in milliseconds without preprocessing [Source] [Source].

Current Status: What Can It Do and How Is It Used?

Currently, the Gemini Decisions API is provided through Google’s developer platform, Google AI Studio (a developer environment where you can experiment with Google’s latest AI models and issue API keys) [Source]. The question types and features supported by this model are designed with exquisite precision:

1. Support for Diverse Question Types: It handles not only typed yes/no and true/false questions, but also multiple-choice questions with up to 255 options, and score/rubric-based evaluation questions divided into up to 255 levels [Source] [Source].
2. Provision of Confidence and Probabilities: Rather than simply stating “The answer is A,” it returns a confidence level between 0 and 1 or score-based probability distributions with every answer [Source] [Source]. This allows developers and enterprises to numerically verify how certain the AI’s judgment is and build hybrid workflows where humans re-examine only items with low confidence.
3. Multimodal Integrated Processing: It supports multimodal inputs (technology that simultaneously understands and processes various forms of information such as text, images, and speech) spanning not only text documents, but also images, audio files, high-definition video, and massive PDF files [Source] [Source]. For example, you can throw 1,000 audit questions at once regarding a one-hour meeting video or a hundreds-page technical whitepaper.

In fact, looking at test cases utilizing small Python-based scripts on three customer reviews, we can see refund eligibility checks, core topic selection, and dissatisfaction score measurement being accurately and in real-time classified through this model [Source].

What Lies Ahead?

The field that will experience the greatest transformation due to the advent of this model is the AI Agent (an autonomous artificial intelligence system that achieves goals by judging for itself and executing tools without human intervention) ecosystem.

Until now, whenever AI agents had to decide their next action in complex environments, they had to go through the cumbersome process of generating long text and having programs parse it again. This process was slow, costly, and error-prone. However, with the popularization of the Decisions API—capable of processing up to 1,000 structured questions in 0.2 seconds—agents will be able to run countless conditional statements and decision loops at ultra-low cost and immense speed every single moment [Source] [Source].

Going forward, enterprises are expected to actively adopt this technology in reviewing massive legal documents, real-time content moderation (management tasks filtering out harmful content), and real-time financial transaction risk detection. A great paradigm shift has already begun—from an era where AI fluently “writes” sentences to an era where it makes correct “choices” accurately, quickly, and cheaply.

MindTickleBytes’ AI Journalist Perspective

Perhaps we have been wasting countless tokens and electrical power trying to make AI write essays all this time. Google’s GeminiDecision1 sharply proves that AI does not need to speak like a poet; its true industrial value is unlocked when it operates as a sophisticated decision-making machine. Beyond text creation competition, it is time to watch how Google’s move targeting the “ultra-fast decision-making market” will further accelerate the brain speed of AI agents.

References

1. Google, Gemini Decisions API, URL: https://blog.google/innovation-and-ai/technology/developers-tools/gemini-decisions-api/
2. Grokipedia, Gemini Decisions API, URL: https://grokipedia.com/page/Gemini_Decisions_API
3. Google AI Studio, Decisions API - Gemini API, URL: https://aistudio.google.com/docs/decisions-api
4. OpenRouter, GeminiDecision1 - API Pricing & Providers, URL: https://openrouter.ai/google/gemini-decision-1
5. YouTube, GeminiDecision1: Google’s AI That Doesn’t Write Text…, URL: https://www.youtube.com/watch?v=UwaJygCdFW8
6. Interesting Engineering, Google unveils Gemini Decisions API to handle 1,000 questions at once, URL: https://interestingengineering.com/ai-robotics/google-gemini-decisions-api-fast-ai-agents
7. SiliconANGLE, Google enters decision model market with Gemini Decisions API, URL: https://siliconangle.com/2026/11/11/google-enters-the-decision-model-market-with-gemini-decisions-api/
8. Macpy, Gemini Decisions API Released: Pricing, Speed, and First Call Guide, URL: https://mcpy.kr/ko/blog/gemini-decisions-api-news
9. YouTube, Google is Back: Gemini 4 Hydrogen, Carbon, Decisions API & Omni, URL: https://www.youtube.com/watch?v=GyUkqLPjYVQ
10. Laozhang, Gemini 3.5 Flash vs Gemini 3.1 Flash-Lite: Gemini API Selection Criteria, URL: https://blog.laozhang.ai/ko/posts/gemini-3-5-flash-vs-gemini-3-1-flash-lite
11. OpenRouter, Gemini 4 Hydrogen - API Pricing & Benchmarks, URL: https://openrouter.ai/google/gemini-4-hydrogen
12. Google AI Studio, Docs - Gemini API, URL: https://aistudio.google.com/docs

13. Google AI for Developers, *Gemini Thinking

    Gemini API*, URL: https://ai.google.dev/gemini-api/docs/thinking?hl=ko

14. YouTube, AINews: Massive Shakeup Rocked The AI World, URL: https://www.youtube.com/watch?v=G_Jrexy_5Bg
15. GIGAZINE, Google releases ‘Gemini Decisions 1,’ an AI model for…, URL: https://gigazine.net/gsc_news/en/20261112-gemini-decisions-1/