Ep. 15 - Should You Use Open Source LLMs or GPT-4?

There is an unending tsunami of news and announcements about new large-language models (LLMs) from large tech providers and the open source community. You're wondering: 

  • Are open source LLMs as good as proprietary ones like GPT-4?
  • What are the pros and cons of open source LLMs?
  • How should I get started?

Prolego CEO, Kevin Dewalt, answers these questions in Episode 15 of our LLM & Generative AI Strategy Series and provides some practical advice. 

In this video, we performed a head-to-head comparison between the proprietary giant GPT-4 and an open-source darling called Phind-CodeLlama-34B-v2 (or let’s just stick with ‘Phind’) on the same Unified Natural Language Query problem we covered in Episode 4.

Here are the key takeaways:

1. GPT-4 vs. Open Source: GPT-4 is still the kingpin for generalized tasks, but open-source models like Phind aren't too far behind. They can be even more efficient in generating complex SQL queries.

2. Pros and Cons: With open source, you retain full data control and gain operational flexibility. This optionality comes at the expense of additional engineering effort. 

3. How to Start: Build a prototype with GPT-4 to check the viability. If things look promising, you can then switch gears to an open-source model for optimization—be it speed, cost, or data privacy.

These examples will help you accelerate your AI program by avoiding the most common mistakes in model selection.

Let’s Future Proof Your Business.