Large Language Model(LLM)
A neural network with billions of parameters trained on broad text corpora to predict and generate language — the engine behind ChatGPT, Claude, and Gemini.
LLMs are transformer-architecture models pre-trained on internet-scale text, then post-trained for instruction-following and helpfulness via RLHF or constitutional AI. In production they're selected on the trade-off between capability (Opus, GPT-4.1, Gemini Ultra), latency/cost (Sonnet, GPT-4o-mini, Haiku, Flash), and context window. For most B2B agent workloads in 2026, Claude Sonnet and GPT-4.1 are the price/quality sweet spots; Opus and Gemini Ultra are reserved for hard reasoning steps.
Related terms
AI systems where an LLM plans and executes multi-step tasks by calling external tools, accessing files, browsing, and adjusting its own approach based on results.
An AI pattern that retrieves relevant documents from a vector database and injects them into the LLM prompt — so the model can answer from custom knowledge it was not trained on.
A capability of modern LLMs where the model emits structured JSON requesting that the host program execute a named tool with arguments — used to give the LLM internet, code execution, database, or any external action.
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