Can Local AI Beat OpenAI? 🤖 Comparing GPT-4o & Llama with Python | Agentic AI Lab 2

Description

Learn how to compare multiple Large Language Models (LLMs) like OpenAI GPT-4o and Ollama’s Llama models in this hands-on Agentic AI Lab 2. We’ll go step-by-step through creating a Python notebook that evaluates different models — measuring speed, quality, and reasoning — all using the OpenAI SDK and Ollama local models. Github link: https://github.com/TEJAPS/agentic-dpoint/blob/main/1-opensdk/Lab2_MultiModel_AgenticAI.ipynb 📘 What you’ll learn in this video: How to integrate multiple LLMs (OpenAI, Ollama, and more) in one workflow Comparing response quality, latency, and reasoning depth Using structured evaluation for model benchmarking Handling API vs Local model interfaces cleanly Extending your code to include Anthropic, Gemini, or Groq models later 🧠 Key Takeaway: Understand how to build multi-model agentic systems that can automatically select the best model for a given task — the foundation of Agentic AI.