Definition
A large language model (LLM) is a deep neural network trained on massive amounts of text to predict the next token in a sequence. Given billions of parameters and billions of training examples, LLMs develop an emergent ability to understand and generate natural language across tasks they were not explicitly trained for: translation, summarization, classification, question-answering, and code generation.
Common examples include GPT-4, Claude, Llama, and Nemotron. They vary in size (7 billion to 400+ billion parameters), training data, alignment approach, and commercial terms. Smaller open-weight models like Nemotron Nano run efficiently on self-hosted GPU servers, making them practical for SaaS products that need to keep customer data inside their own infrastructure.
How SheetLinkWP relates to Large Language Model
SheetLink Forms uses Nvidia's Nemotron Nano model, self-hosted on a dedicated GPU server, for AI Lead Scoring and AI Analytics. Because the inference runs on infrastructure we control, your form data never touches OpenAI, Anthropic, or any other third-party API. We chose a smaller, fast model over a frontier model because the classification task is well-scoped and does not require the broadest capability - it requires fast, private, reliable inference.