Whether you’re building chatbots, automating workflows, or developing AI-driven apps, the right AI model can make a huge difference in performance, security, and cost.
This post is still a work in progress as I experiment with different models, implement various use cases, and try to understand concepts like evaluation (evals).
When choosing an AI model, data privacy should be a key factor. If you’re working with sensitive or proprietary data, you might prefer an open-source, self-hosted model like LLaMA or Mistral to ensure full control over data.
Cloud-based models like OpenAI’s GPT-4 or AWS Bedrock handle data differently, often with retention policies or logging mechanisms, so be sure to review their documentation and terms before implementation.
This is not a complete list, as the AI landscape is constantly evolving. Here are some additional AI models worth considering:
Check the following link (super recommended) for an updated list MetaSchool’s AI Models Directory.
Choosing the right AI model is an iterating process, and I’m continuing to explore/experimenting these options myself. If you’re also testing different models, let’s exchange insights!