Podcast: Choosing the Right LLM for Your Business - 10Pearls

Performance

Performance can be gauged broadly in two categories: speed and precision.

• Inference speed
  Speed determines how quickly an LLM processes information and provides an output. This is especially important for chatbots, where immediate turnaround is expected.
• Precision
  While speed is one of the most important aspects of an LLM, precision is equally important. There’s no use in getting quick responses if they’re factually incorrect.

Model dimensions

Model dimension can be explained as a model’s brain power and memory, which can be gauged by a model’s size and context length. speed and precision.

• Context length
  Context length can be defined as a model’s short-term memory. It defines how much a model can retain and reference information. Larger context length requires a model to “remember” and have contextually relevant conversations.
• Model size
  This can be measured in billions of parameters and is a generic indicator of a model’s complexity and capability. Larger models tend to be more sophisticated, with the ability to process billions of data points within training a model.

Usage rights

These are the licensing terms and restrictions for using and modifying a model. Proprietary LLMs provide robust infrastructure and restrictive terms of service, with less flexibility for customization. In contrast, open-source models offer greater flexibility and added maintenance and security responsibilities.

Cost

Cost encompasses both the upfront and ongoing expenses associated with an LLM. Businesses should evaluate these costs in the context of their budget and long-term scalability requirements.

• Direct costs
  Subscription fees or usage-based pricing for paid models are direct costs. While the cost per token starts at an affordable rate, it can add up quickly with higher volumes of tokens used.
• Indirect costs
  While an open-source model does not have a subscription fee, other indirect costs, such as infrastructure, customization, and maintenance expenses, must be considered.

Scalability

This comes down to an LLM’s ability to handle an increasing user load and demand. While open-source models can be customized to offer tailored solutions for your business, paid models often offer better scalability due to cloud infrastructure.

Data privacy

While open-source models are bound by legalities related to data privacy, they will have access to your data. While developing a personalized open-source model allows hosting it on private servers for greater data control, it requires a robust infrastructure and could be costly.