The pricing model for LLM APIs based on the number of tokens (text units) processed in inputs and outputs.
Token cost is the practical “meter” behind AI usage: longer prompts, longer outputs, and repeated calls usually cost more. The main cost-control lever is to minimise unnecessary text while keeping outputs reliable.
Browse related definitions in the same glossary category.
AI Grounding
Techniques to anchor AI outputs in verified sources and facts, reducing hallucinations and improving reliability.
AI Hallucination
A phenomenon where a large language model generates false or illogical information but presents it as fact.
Citation Confidence
A measure of how accurately an AI model attributes information to its original source.
Content Provenance (C2PA)
Technical standards for verifying the origin and authenticity of digital content, increasingly important for AI-generated media.
Embeddings
Numerical representations of text, images, or other data that capture semantic meaning, enabling similarity search and machine learning.
Fine-Tuning
Adapting a pre-trained AI model to a specific task or domain by training it on additional specialised data.
Related GEO services, audits, and frameworks that operationalise Token Cost in commercial execution.
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