# LLM Optimization (LLMO)

> Optimizing content for how large language models evaluate, trust and select it as a source — a practitioner sibling of GEO and AEO.

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- **term:** LLM Optimization (LLMO)
- **category:** optimization
- **short_def:** Optimizing content for how large language models evaluate, trust and select it as a source — a practitioner sibling of GEO and AEO.
- **long_def:** LLMO (sometimes AIO, AI Optimization) focuses specifically on large-language-model citation behavior: clear claims, source-able facts, structure a model can parse. It shares roughly 80% of its methods with GEO; the main difference is provenance and scope — GEO came from academia and covers all generative engines, LLMO arose among practitioners and targets LLMs specifically.
- **see_also:** geo, aeo, share-of-model
- **etymology_origin:** — (verify-against-primary-at-build)
- **related_to:** geo, aeo, share-of-model, agentic-seo
- **contrast_with:** Unlike GEO, which the founding paper scopes to all generative engines, LLMO is the practitioner framing aimed specifically at large language models — but the two share roughly 80% of their methods and are often used interchangeably.
- **example:** Industry commentary (e.g. Ahrefs, 2025) argues GEO, LLMO and AEO are largely the same practice under different names — 'it's all just SEO'.
- **source:** https://ahrefs.com/blog/geo-is-just-seo/
- **status:** active
- **why_it_matters:** LLMO is one of several near-synonyms a site owner will encounter; disambiguating it from GEO and AEO prevents chasing three 'different' strategies that are really one.
- **sameAs:** —
- **bridge_entity:** geo
- **last_verified:** 2026-06-15
- **md_twin:** /glossary/llmo.md