How to Choose Base Model for Your LLM Application 🧐?

The field of Large Language Models (LLMs) is flourishing with numerous models, continuously evolving day-by-day. If you want to develop an LLM application for production, which model on the market should you choose?

Should we prioritize the best-performing model on the market? GPT-4 undoubtedly stands out as a top contender.

Should we consider privacy-aware LLMs due to the paramount concerns surrounding data privacy these days? An viable option can be the GPT4ALL as we introduced earlier.

Or should we consider an open-source that is fine-tunable like Google’s T5?

Complexity of LLMs

Dimensions of consideration

To summarize, your checklist should encompass careful consideration of the tradeoffs among the following essential dimensions:

• “Out-of-the-box quality for your specific task.
• Inference speed and latency to ensure optimal performance.
• Cost implications that align with your budget and resources.
• Fine-tuneability and extensibility for a customized fit to your requirements.
• Data security and privacy measures to safeguard sensitive information.
• License permissibility, ensuring compliance with licensing…