What is an LLM (Large Language Model)?
LLMs are AI systems trained on massive text datasets to understand and generate human-like text, powering ChatGPT, Claude, and other AI assistants.
LLMs are the foundation of modern AI assistants like ChatGPT, Claude, and Gemini. These models learn patterns from massive text datasets - including websites, books, and articles - to predict and generate text. When you ask an LLM a question, it draws on this learned knowledge to formulate a response, making it feel like you're conversing with a knowledgeable assistant.
Why it matters
LLMs matter for brands because they're becoming a primary interface between consumers and information. When millions of people ask LLMs for product recommendations, travel advice, or business solutions, the model's training determines which brands get mentioned. Understanding how LLMs work helps brands develop effective AI visibility strategies. The key insight: LLMs learn from data, so your presence and portrayal in quality, widely-referenced sources shapes how AI discusses your brand.
What people get wrong
- LLMs search the internet for answers. Base LLMs generate responses from patterns learned during training. Web search capabilities (like Perplexity) are separate features layered on top.
- LLMs understand and think like humans. LLMs are sophisticated pattern matchers. They produce human-like text without human-like understanding or consciousness.
- All LLMs are basically the same. Different LLMs have different training data, architectures, and fine-tuning. They can give quite different answers to the same question.
Related terms
ChatGPT: ChatGPT is the most popular consumer application built on LLM technology.
Training Data: Training data is what LLMs learn from, determining their knowledge including brand awareness.
Hallucination: Hallucination is when LLMs generate plausible but incorrect information - a key limitation to understand.
GPT: GPT is the specific LLM architecture developed by OpenAI, one of the most influential model families.
Monitor your brand across all major LLMs
Trakkr tracks how different LLMs discuss your brand. See how ChatGPT, Claude, and Gemini each describe you, compare mentions over time, and identify discrepancies across platforms.
To connect large language models with the way brands earn answers, start with a plain-language explanation of AEO and then return to the model mechanics.
The terms are often used together. See where AEO and GEO overlap and differ before assigning each one a separate strategy.
Frequently Asked Questions
What's the difference between an LLM and AI?
AI is a broad field. LLMs are a specific type of AI focused on language understanding and generation. Not all AI is LLM-based, but most conversational AI assistants use LLMs.
Can I get my brand into an LLM's training data?
You can't directly add to training data, but creating quality content on authoritative sites increases the chance of inclusion in future training datasets.
Why do different LLMs say different things about my brand?
Each LLM is trained on different data at different times, and fine-tuned differently. This leads to variations in how they discuss brands.
How often are LLMs updated with new information?
Major model updates happen every 6-18 months. Some LLMs also have web search capabilities that access current information.