Glossary term
Token
The basic unit of text processed by language models, roughly equivalent to a word or word fragment.
What it is
The basic unit of text processed by language models, roughly equivalent to a word or word fragment. In OdysseyGPT, Token matters because it turns raw documents into cited, reviewable outputs instead of opaque model responses.
Key Takeaways
- The basic unit of text processed by language models, roughly equivalent to a word or word fragment.
- Token is most useful when accuracy must be verified against source documents.
- OdysseyGPT applies token in governed document workflows rather than open-ended prompting alone.
Why it matters
A token is the fundamental unit of text that language models process. Tokens are created by tokenizers that split text into manageable pieces - common words become single tokens while rare words may split into multiple tokens. On average, one token is about 4 characters or 0.75 words. Token counts determine context window usage and API costs. Understanding tokenization helps predict model behavior and optimize prompts.
How OdysseyGPT uses it
OdysseyGPT manages tokenization internally to optimize processing. We track token usage for context construction, ensuring retrieved passages fit within model limits while maximizing relevant content. Our pricing and metering are based on document pages rather than tokens, simplifying cost prediction for customers.
Evaluation questions
What is Token?
A token is the fundamental unit of text that language models process. Tokens are created by tokenizers that split text into manageable pieces - common words become single tokens while rare words may split into multiple tokens. On average, one token is about 4 characters or 0.75 words. Token counts determine context window usage and API costs. Understanding tokenization helps predict model behavior and optimize prompts.
Why does Token matter in enterprise document workflows?
Token matters because high-stakes teams need reliable retrieval, defensible outputs, and consistent review behavior across large document collections.
How does OdysseyGPT use Token?
OdysseyGPT manages tokenization internally to optimize processing. We track token usage for context construction, ensuring retrieved passages fit within model limits while maximizing relevant content. Our pricing and metering are based on document pages rather than tokens, simplifying cost prediction for customers.