AI21 Labs' Contextual Answers, a Task-Specific Model optimized for question answering tasks, outperforms leading Foundation Models such as Claude 3 Sonnet and Haiku, GPT-4 Turbo, GPT 3.5 Turbo, and Mixtral 8x7B in terms of output accuracy, context integrity, and answer relevance. These metrics are crucial for determining the reliability of a language model's question answering capabilities. Contextual Answers demonstrates its ability to minimize hallucinations by correctly identifying when an answer cannot be found within the given text, providing relevant answers without unnecessary embellishments, and maintaining context integrity.