What is LLM (Large Language Model)?
LLM (Large Language Model) — A foundational AI model trained on vast amounts of text data to understand and generate human-like language.
LLMs like GPT-4, Claude, and Llama are trained on billions of text samples to predict the next word in a sequence. This simple training objective produces models capable of summarization, translation, code generation, and complex reasoning. Enterprise adoption requires careful evaluation of model size, latency, cost, and data privacy implications.
Frequently Asked Questions
What is the difference between an LLM and traditional AI?
Traditional AI systems are built for specific tasks with structured data. LLMs are general-purpose models that understand and generate natural language, making them adaptable to a wide range of tasks without retraining.
Can LLMs be run on-premise?
Yes. Open-weight models like Llama and Mistral can be deployed on your own infrastructure, giving you full control over data privacy and compliance.
How much does it cost to run an LLM?
Costs vary dramatically. Cloud API calls can range from fractions of a cent to several dollars per request depending on model size. Self-hosted models require significant GPU investment upfront but reduce per-query costs at scale.