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 runs AI Lead Scoring and AI Analytics on OpenAI's models via the OpenRouter API gateway (routing pinned to OpenAI), with Google's Gemini API as an automatic failover - all named as sub-processors in our privacy policy, and none of them train on your data. BYOK mode routes inference through your own OpenAI or Gemini key instead. The scoring task is well-scoped classification, so it needs fast, reliable inference rather than the broadest frontier capability.