Model benchmarking
The LLM itself is a fundamental component of any intelligent application. Given that there are many LLMs that may be suitable for your application, it is helpful to compare them to each other to see which will best serve your application. To compare multiple models, you can assess them all against a standard set of evaluations. This process of comparing models across a uniform set of evaluations is called model benchmarking. Benchmarking can help you understand the model’s capabilities and limitations.
Often, the LLMs that perform best on benchmarks are the largest models, such as GPT-4 and Claude 3 Opus. However, these larger models also tend to be more expensive to run and slow to generate, compared to smaller models, such as GPT-4o mini and Claude 3 Haiku.
Even if the larger models are prohibitively expensive, it can still be helpful to use them when developing your application since they set a baseline of ideal system performance. You can design...
