OpenAI’s GPT-4o vs. Gemini 1.5 ⭐ Context Memory Evaluation
A Large Language Model’s (LLM) ability to find and understand detailed information within large context windows is a need-to-have these days.
The Needle in the Haystack test stands as a crucial benchmark for assessing large language models for such tasks.
In this article, I will present my independent analysis measuring context-based understanding of the top-tier LLMs from OpenAI and Google.
Which LLM should you use for long-context tasks?
What is a “Needle in the Haystack” Test? 🕵️♂️
A “Needle in the Haystack” test for large language models (LLMs) involves placing a specific piece of information (the “needle”) within an extensive chunk of unrelated text (the “haystack”).
The LLM is then tasked to respond to a query that requires extracting the needle.
Such a test is used to evaluate an LLM’s proficiency in context comprehension and information retrieval from long contexts.
Successfully replying to the query showcases a detailed understanding of the context, which is crucial for developing applications around context-based LLMs.
