Understand key differences, strengths, and use cases of each prompting style
Last Updated: September 18, 2025

Prompt engineering maximizes the potential of Large Language Models (LLMs) like ChatGPT by crafting precise instructions or cues that guide LLMs to generate coherent and contextual responses.

As we explore prompt engineering further, two prominent techniques stand out: Zero-Shot Prompting and Few-Shot Prompting. In this infographic, we will delve into the details of these techniques and how they differ from each other.

To view this infographic in high resolution, click here.

A Comparative Analysis of Zero Shot Vs Few Shot Prompting

Maximize Your LLM Potential With the Powerful Prompting Techniques!

Both zero-shot and few-shot prompting are game-changing techniques in prompt engineering. While zero-shot prompting enables quick and efficient responses without specific training, few-shot prompting fine-tunes the model with minimal examples for enhanced accuracy.

If you want to dig deeper into their distinguished use cases and how they empower businesses to streamline their customer support workflows, refer to this infographic.

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