What is LLM optimization (LLMO)?

By the Variask team · Updated

Definition

LLM optimization, or LLMO, is the work of improving how large language models describe and recommend your brand. It is another name for much of what GEO and AEO cover, with extra focus on what models learn in training as well as what they find through search.

Also called LLMO, Large language model optimization

How it works

  • Make your brand facts clear and consistent across the web.
  • Earn mentions on widely read, trusted sources.
  • Publish clear pages AI can read and quote.
  • Measure what models say over time.

What it means for brands

  • LLMO, GEO and AEO are mostly the same work under different names.
  • Training data changes slowly, so consistent facts over time matter.
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Questions

LLM optimization (LLMO):
common questions

Mostly in emphasis. LLMO talks about the models themselves, GEO about generative answers. The practical work overlaps heavily.

Not directly. You can improve the sources it learns from and the pages it finds through search.

Related terms

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Disciplines

Generative engine optimization (GEO)

Generative engine optimization (GEO) is the practice of making your brand and content more likely to be mentioned, cited and recommended in answers written by AI assistants.

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Disciplines

Answer engine optimization (AEO)

Answer engine optimization (AEO) is the practice of getting your brand chosen as the answer by answer engines: AI assistants, AI search features and voice assistants that reply directly instead of showing a list of links.

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How AI search works

Large language model (LLM)

A large language model (LLM) is an AI model trained on very large amounts of text to understand and write language. LLMs power assistants such as ChatGPT, Gemini, Claude, Grok and DeepSeek.

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Full glossary