LabelLLM vs Prodigy

LabelLLM has no write-up on Specifiction yet; its figures are above.

Prodigy is a downloadable developer tool and Python library for creating training and evaluation data for machine-learning models. Its built-in recipes cover named entity recognition, text classification, computer vision, audio and video annotation, transcription, and model training and evaluation. A customizable web application offers 23 interfaces for work with text, images, audio, video, relations, multiple choice, HTML and conflict resolution. Users can define workflows with Python recipes and create interfaces using HTML, CSS and JavaScript. Prodigy supports spaCy, plugins for Hugging Face models and integrations with major LLM API providers. Data can be stored in SQLite, MySQL or PostgreSQL and exported to JSON. It runs on the user's own machines without connecting to the maker's or third-party servers, including on air-gapped machines. The standard Python web server and app can be deployed in the cloud or on-premise. Personal licensing costs $390, paid once, excluding tax; Company licensing costs $490, paid once per seat in packs of five, excluding tax.