WhisperNER is a unified model that combines Automatic Speech Recognition (ASR) and Named Entity Recognition (NER), equipped with zero-shot capabilities. This model is designed as a robust foundational model for downstream tasks of ASR with NER and can be fine-tuned on specific datasets to enhance performance. The significance of WhisperNER lies in its ability to simultaneously handle speech recognition and entity recognition tasks, improving efficiency and accuracy, especially in multilingual and cross-domain scenarios.