# What Is LLMO (Large Language Model Optimization)?

> What LLMO (large language model optimization) is, how it differs from GEO and what a store can control about what ChatGPT says about it.

URL: https://clione.ai/glossary/llmo/
Lang: en

LLMO, optimization for an [LLM (large language model)](/glossary/llm/), sounds like a new discipline, but it describes almost the same work as [GEO (Generative Engine Optimization)](/glossary/geo/). So the useful question is not what LLMO is in the abstract but **what it adds to GEO**. The short answer is one thing: an assistant can talk about your products without having visited your site that day, using what it learned in training, and that is the part the name LLMO puts up front.

## How a brand gets into an answer

A language model can answer by two routes, and it often uses both at once.

**What it learned in training.** To gather training data, the companies that build models crawl the web. OpenAI, for example, does it with [GPTBot](/glossary/gptbot/): it crawls content that may be used to train its foundation models, and blocking it in [robots.txt](/glossary/robots-txt/) signals that your site's content should not be used for that training.[^openai-bots] At Google, the equivalent control is [Google-Extended](/glossary/google-extended/), which serves to limit training and [grounding](/glossary/grounding/) in some of Google's other systems.[^google-ai-features]

**What it searches for in the moment.** ChatGPT can search the web automatically when a question benefits from current information, and the answer may then carry citations to its sources. To search, it **rewrites your question into one or more more specific queries** that it sends to its search providers.[^openai-search-help] The sites it shows are crawled by a different agent, [OAI-SearchBot](/glossary/oai-searchbot/): if you block it, your site does not appear in ChatGPT's search answers, although it can still show up as a navigation link.[^openai-bots]

The two routes mix in shopping. To decide which products to show, ChatGPT takes into account structured metadata from first- and third-party providers, such as price or description, and also **the answers the model itself generates before looking at new search results**.[^openai-shopping-help] Put another way: what the model already "believes" about a product goes into the answer before it searches for anything.

## What LLMO adds to GEO

GEO has a precise origin: a research paper published on arXiv on November 16, 2023 and accepted at KDD 2024, which defines [generative engines](/glossary/generative-engine/) as systems that answer by **synthesizing information from several sources and summarizing it with an LLM**.[^geo-paper] That is, GEO was born thinking about the second route, the sources the engine retrieves and cites.

LLMO has no equivalent document. Google's guide to optimizing for generative search names [AEO (Answer Engine Optimization)](/glossary/aeo/) and GEO as terms used for the work of improving visibility in [AI search](/glossary/ai-search/), and answers that, for Google Search, it is still SEO; LLMO does not appear.[^google-ai-guide] What LLMO has of its own is the first route, training, and there **a store controls little, and late**: it can decide whether to let the training agents crawl, but none of the OpenAI pages cited here says how often its models are trained or how a particular page gets into them.[^openai-bots]

## In a store

The most concrete setting that separates LLMO from GEO lives in `robots.txt`. OpenAI gives this case as its example: allow OAI-SearchBot to appear in [ChatGPT search](/glossary/chatgpt-search/) and block GPTBot so that what it crawls is not used for training, because **each setting is independent of the other**.[^openai-bots] In a **fictional example** store, it would look like this:

```text
User-agent: OAI-SearchBot
Allow: /

User-agent: GPTBot
Disallow: /
```

With this file, the store can get cited when ChatGPT searches, but it asks that its content stay out of training. It is an LLMO decision in its purest form: it changes nothing about what ChatGPT finds today when it searches, and it decides whether your product pages can become part of what its models know tomorrow. For a purchase question, the first block weighs more: ChatGPT searches the web when a question benefits from current information, and today's price and stock only arrive by that route.[^openai-search-help]


That blocking GPTBot takes your store out of ChatGPT. It does not: GPTBot is the training [crawler](/glossary/web-crawler/), and what decides whether you appear in ChatGPT's search answers is OAI-SearchBot. OpenAI says it without ambiguity: **each setting is independent**, and you can allow one and block the other.[^openai-bots] The reverse fails too: letting GPTBot through does not get you into search answers if you block OAI-SearchBot.[^openai-bots]


## How to check it

1. **Open your `robots.txt`** and see what you do with GPTBot and with OAI-SearchBot, separately. A change can take about 24 hours to show in ChatGPT search.[^openai-bots]
2. **Ask ChatGPT about your product in a new chat** and see whether the answer brings citations or sources. Answers that use search can include citations; an answer with none probably came from what the model already knew.[^openai-search-help]
3. **Repeat the question choosing the search tool** and compare the two answers with your [product page](/glossary/product-page/).[^openai-search-help]
4. **Check that your product [structured data](/glossary/structured-data/) is complete**: price and description are part of what ChatGPT takes into account when choosing products.[^openai-shopping-help]
5. **When you get an LLMO proposal, ask which route it works on** and how it will measure it. Google warns that no third-party tool has access to its internal ranking or AI systems.[^google-ai-guide]

## Related concept: GEO

GEO has an origin paper and Google names it in its guide;[^google-ai-guide] LLMO is its model-centered variant. In practice they share almost everything: that your page can be crawled, indexed and cited, and that it says something of its own. GEO is measured in citations inside answers composed from retrieved sources;[^geo-paper] LLMO adds the question of what the model knows about you without searching, and no report from the platforms cited here answers that: you answer it by asking, as in step 2. If a proposal uses both names, what matters is whether it includes that second question and how it plans to answer it.

To keep going, the comparison [GEO, AEO and SEO: what changes for an online store](/comparisons/geo-aeo-seo/) puts the names side by side, and the [AI search reading path](/learn/ai-search/) orders the rest of the terms.