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Samsung · AI / ML · Filed Jul 16, 2025 · USPTO published Jun 25, 2026 · Jun 25 release

Samsung Patents AI That Serves Paying Customers' Prompts Before Free Users

Not all AI requests are created equal. Samsung's new patent describes a system that recognizes this and acts on it, routing some prompts to the front of the line while others wait their turn.

By · Updated · 3 min read

Samsung Patent: AI Prompt Priority Queue System, figure from US 2026/0178374 A1
Figure from the official USPTO publication.
Publication number
US 2026/0178374 A1(US20260178374A1)
Applicant
Samsung Electronics Co., Ltd.
Filed · Published
Jul 16, 2025 · Jun 25, 2026
Inventors
Zhaoyuan Su, Jingoo Han, Joon Hee Choi, Yue Cheng, Ali Anwar, Sam Fountain
Status when we published
Waiting for an examiner
Document
20 claims
US classification
718/101
Parent application
Claims priority from a provisional application 63737223 (filed Dec 20, 2024)
AI vision

What Samsung's AI prompt priority system actually does

Imagine a hospital emergency room: a broken arm waits while a heart attack gets seen immediately. Samsung's patent applies that same logic to AI systems. When multiple people send requests to the same AI model at the same time, this system checks the "priority level" of each request before deciding how to process it.

A high-priority request, say from a paying subscriber or a time-sensitive business application, gets processed with settings tuned for speed. A lower-priority request might get bundled together with others into a larger batch, which is more efficient but slightly slower.

The result is that an AI service can serve different customers differently without running separate AI models for each tier. It's the same engine under the hood, but the traffic rules change depending on who's asking.

How the system assigns batch sizes by service level

The patent describes a processor that receives multiple inputs (prompts) destined for the same AI model. Before the model touches any of them, the system reads a service level attached to each input, essentially a tag that indicates how urgently or preferentially that request should be handled.

Based on those service levels, the system sets two key variables for each input:

  • Processing criterion: rules about how the model should handle the request (for example, whether to use a faster but less thorough inference path)
  • Batch size: how many requests are grouped together before the model processes them (batching, or grouping requests, improves hardware efficiency but can add wait time)

A high-priority input might get a small batch size (processed almost immediately, alone or with very few others) and a fast processing criterion. A low-priority input might be held until a larger batch accumulates, which saves compute costs but takes longer.

The patent also references two separate memory components, suggesting the system is designed with real hardware deployment in mind, likely targeting on-device or edge AI inference rather than purely cloud infrastructure.

What this means for AI services running at scale

For companies running AI services commercially, this kind of tiered processing is the difference between profitable infrastructure and runaway compute bills. Without priority queuing, every request competes equally for the same hardware, which means you either over-provision (expensive) or your best customers experience the same slowdowns as free-tier users.

For you as a user, this could mean that a paid AI subscription actually feels noticeably faster than a free one, not because the underlying model is different, but because your requests skip the queue. Samsung's Galaxy AI features and its broader push into on-device AI make this a practical concern, not a theoretical one.

Source: US 2026/0178374 A1 at the USPTO (PDF). Full patent text and figures are in the official publication.

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