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AIF-C01 · Question #34

A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible. Which solution will meet these requirements?

The correct answer is A. Deploy optimized small language models (SLMs) on edge devices. To achieve the lowest latency possible for inference on edge devices, deploying optimized small language models (SLMs) is the most effective solution. SLMs require fewer resources and have faster inference times, making them ideal for deployment on edge devices where processing…

Submitted by ashley.k· Mar 30, 2026

Question

A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible. Which solution will meet these requirements?

Options

  • ADeploy optimized small language models (SLMs) on edge devices.
  • BDeploy optimized large language models (LLMs) on edge devices.
  • CIncorporate a centralized small language model (SLM) API for asynchronous communication with
  • DIncorporate a centralized large language model (LLM) API for asynchronous communication with

How the community answered

(49 responses)
  • A
    82% (40)
  • B
    10% (5)
  • C
    6% (3)
  • D
    2% (1)

Explanation

To achieve the lowest latency possible for inference on edge devices, deploying optimized small language models (SLMs) is the most effective solution. SLMs require fewer resources and have faster inference times, making them ideal for deployment on edge devices where processing power and memory are limited.

Topics

#Edge AI#SLM deployment#Low-latency inference

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