GEO vs LLMO: What's the Difference? | Definition and Overview
The difference between GEO and LLMO refers to the distinctions between two strategies that both aim to get content recognized by generative AI, but differ in the scope of AI platforms they target.
LLMO refers to optimization for large language models like ChatGPT and Claude, while GEO covers all generative AI engines, including Google AI Overviews and Perplexity.
With multiple terms now in circulation, understanding the precise definition of each is essential for building a focused strategy.
What You'll Learn in This Article
The definition of LLMO and how its scope differs from GEO
The relationship between GEO and LLMO (GEO as the broader concept)
A comparison of five AI search-related terms
The shared optimization principles behind GEO and LLMO
LLMO (Large Language Model Optimisation) is the practice of optimizing your content so that large language models like ChatGPT and Claude cite or mention it in their AI-generated responses.
LLMO is more narrowly scoped than GEO.
While LLMO focuses specifically on large language models, GEO is a broader concept that also covers AI-powered search engines beyond LLMs.
2. GEO vs LLMO: Key Differences
GEO is a broader concept that includes LLMO. The diagram and table below map out the relationship and key differences.
The Relationship Between GEO and LLMO
※ Created in-house based on publicly available information
According to Figment Agency (Emma Grant), the key differences between GEO and LLMO can be summarized as follows:
GEO vs LLMO Comparison
Factor
GEO
LLMO
Scope
All generative AI engines
Large language models only
Platforms
Google AI Overviews, Perplexity, Copilot, ChatGPT, Claude, Gemini
ChatGPT, Claude, Gemini
Relationship
Broader concept that includes LLMO
A subset of GEO
Goal
Be featured in AI-assisted search results
Appear in AI-generated responses
In practice, GEO and LLMO are addressed through largely the same tactics.
"GEO" has become the more widely used term across the industry.
3. Five AI Search Terms, Explained
As AI search has grown, several overlapping terms have emerged. The table below provides a clear breakdown of all five.
Five AI Search-Related Terms Compared
Term
Focus
Platform Examples
Purpose
LLMO
Large language models
ChatGPT, Claude, Gemini
Appear in AI-generated responses
GEO
Generative AI engines (broader)
Google AI Overviews, Perplexity, Copilot
Be featured in AI-assisted search results
AI Optimisation / AI SEO
AI visibility (general)
All of the above
Umbrella term for all AI-related visibility strategies
AEO
Answer engines
Search engines + AI tools
Be the trusted answer when people search
Traditional SEO
Keyword + link-based search
Google, Bing, Yahoo
Rank web pages in search results
These are overlapping strategies, not competing ones.
Understanding the distinctions helps you decide where to focus your efforts.
4. What GEO and LLMO Have in Common
Figment Agency's article captures the shared essence of GEO and LLMO optimization:
Getting found in AI-generated answers is less about understanding algorithms and more about earning trust – from users and from machines.
Ahrefs takes the position that "GEO is just SEO" — the fundamentals of quality, relevance, and authority apply regardless of where the content appears.
The following three tactics are considered effective for both GEO and LLMO:
Lead with clear, concise answers: LLMs are considered to prioritize reliable, well-structured information. Answering one key question per section is considered effective.
Demonstrate E-E-A-T: Including author credentials, reputable citations, and verified expertise signals is considered important for earning LLM trust.
Structure content for AI interpretation: Headings, bullet points, FAQs, and definition sentences make content easier for LLMs to parse and cite.
For a practical guide to implementation, see How to Get Started with GEO.
With the GEO tool Genview, you can monitor your AI citation status across platforms relevant to both GEO and LLMO.
Frequently Asked Questions
Q: Should I prioritize GEO or LLMO?
A: GEO is recommended as the priority. Since GEO is a broader concept that includes LLMO, implementing GEO strategy covers LLMO at the same time. The wider platform coverage also means greater potential for brand visibility.
Q: Do GEO and LLMO require different tactics?
A: The tactics are largely the same. Clear content structure, E-E-A-T signals, and AI-readable formatting are effective for both. While the target platforms differ, content-level optimization applies equally across both strategies.
Q: If I'm already doing SEO, does that cover GEO and LLMO?
A: Partially, but GEO and LLMO require additional tactics. Ahrefs argues that quality, relevance, and authority remain the core principles regardless of channel. However, GEO-specific structures — such as BLUF, definition sentences, and FAQ sections — are needed as additional steps.