In this article, you will learn how to build a side-by-side benchmark of local and cloud LLM classifiers using Scikit-Ollama and a Groq-backed Scikit-LLM pipeline.

Topics we will cover include:

How to set up Ollama, Scikit-Ollama, and Scikit-LLM, and how to create a small sentiment dataset for testing.

How to write a reusable helper function that measures the execution time and accuracy of a zero-shot classifier.

How to run the same benchmark locally and through the Groq API, and what the tradeoffs are in latency, cost, setup, and privacy.

Introduction

Looking for a practical, side-by-side comparison of two LLM solutions (local vs. cloud) in the same application scenario?…